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Treatment planning for photodynamic therapy of abscess cavities using patient-specific optical properties measured prior to illumination Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-28 Zihao Li, Md Nafiz Hannan, Ashwani K Sharma, Timothy M Baran
Photodynamic therapy (PDT) is an effective antimicrobial therapy that we used to treat human abscess cavities in a Phase 1 clinical trial. This trial included pre-PDT measurements of abscess optical properties, which affect light dose (light fluence) at the abscess wall and PDT response. This study simulated PDT treatment planning for 13 subjects that received optical spectroscopy prior to clinical
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An adaptive h-refinement method for the boundary element fast multipole method for quasi-static electromagnetic modeling Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-28 William A Wartman, Konstantin Weise, Manas Rachh, Leah Morales, Zhi-De Deng, Aapo Nummenmaa, Sergey N Makaroff
Objective. In our recent work pertinent to modeling of brain stimulation and neurophysiological recordings, substantial modeling errors in the computed electric field and potential have sometimes been observed for standard multi-compartment head models. The goal of this study is to quantify those errors and, further, eliminate them through an adaptive mesh refinement (AMR) algorithm. The study concentrates
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Recovery of the spatially-variant deformations in dual-panel PET reconstructions using deep-learning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-28 Juhi Raj, Maël Millardet, Srilalan Krishnamoorthy, Joel S Karp, Suleman Surti, Samuel Matej
Dual panel PET systems, such as Breast-PET (B-PET) scanner, exhibit strong asymmetric and anisotropic spatially-variant deformations in the reconstructed images due to the limited-angle data and strong depth of interaction effects for the oblique LORs inherent in such systems. In our previous work, we studied time-of-flight (TOF) effects and image-based spatially-variant PSF resolution models within
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Affine medical image registration with fusion feature mapping in local and global Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-28 Wei Ji, Feng Yang
Objective. Medical image affine registration is a crucial basis before using deformable registration. On the one hand, the traditional affine registration methods based on step-by-step optimization are very time-consuming, so these methods are not compatible with most real-time medical applications. On the other hand, convolutional neural networks are limited in modeling long-range spatial relationships
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Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-28 Wanli Zhang, Fangrong Liang, Yue Zhao, Jiamin Li, Chutong He, Yandong Zhao, Shengsheng Lai, Yongzhou Xu, Wenshuang Ding, Xinhua Wei, Xinqing Jiang, Ruimeng Yang, Xin Zhen
Objective. To investigate the incremental value of quantitative stratified apparent diffusion coefficient (ADC) defined tumor habitats for differentiating triple negative breast cancer (TNBC) from non-TNBC on multiparametric MRI (mpMRI) based feature-fusion radiomics (RFF) model. Approach. 466 breast cancer patients (54 TNBC, 412 non-TNBC) who underwent routine breast MRIs in our hospital were retrospectively
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An iterative reconstruction algorithm for unsupervised PET image Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-27 Siqi Wang, Bing Liu, Furan Xie, Li Chai
Objective. In recent years, convolutional neural networks (CNNs) have shown great potential in positron emission tomography (PET) image reconstruction. However, most of them rely on many low-quality and high-quality reference PET image pairs for training, which are not always feasible in clinical practice. On the other hand, many works improve the quality of PET image reconstruction by adding explicit
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Towards liquid EPR dosimetry using nitroxides in aqueous solution Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-27 Sebastian Höfel, Felix Zwicker, Michael K Fix, Malte Drescher
Objective. Water-equivalent dosimeters are desirable for dosimetry in radiotherapy. The present work investigates basic characteristics of novel aqueous detector materials and presents a signal loss approach for electron paramagnetic resonance (EPR) dosimetry. Approach. The proposed principle is based on the radiation dose dependent annihilation of EPR active nitroxides (NO·) in aqueous solutions.
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Time-of-flight scatter rejection in x-ray radiography Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-27 J Rossignol, G Bélanger, D Gaudreault, A C Therrien, Y Bérubé-Lauziére, R Fontaine
Objective. Time-of-flight (TOF) scatter rejection allows for identifying and discarding scattered photons without the use of an anti-scatter grid (ASG). Although TOF scatter rejection was initially presented for cone-beam computed tomography, we propose, herein, to extend this approach to x-ray radiography. This work aims to evaluate with simulations if TOF scatter rejection can outperform ASGs for
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Motion-artifact-augmented pseudo-label network for semi-supervised brain tumor segmentation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-26 Guangcan Qu, Beichen Lu, Jialin Shi, Ziyi Wang, Yaping Yuan, Yifan Xia, Zhifang Pan, Yezhi Lin
MRI image segmentation is widely used in clinical practice as a prerequisite and a key for diagnosing brain tumors. The quest for an accurate automated segmentation method for brain tumor images, aiming to ease clinical doctors’ workload, has gained significant attention as a research focal point. Despite the success of fully supervised methods in brain tumor segmentation, challenges remain. Due to
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Impact of MRI RF coil design on the RF-induced heating of medical implants: fixed B 1 + rms exposure versus normal operating mode Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-26 Aiping Yao, Zihan Li, Mingjuan Ma
A direct comparison of the impact of RF coil design under specific absorption rate and B1+rms limitations are investigated and quantified using RF coils of different geometries and topologies at 64 MHz and 128 MHz. The RF-induced in vivo electric field and power deposition of a 50 cm long pacemaker and 55 cm long deep brain stimulator (DBS) are evaluated within two anatomical models exposed with these
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Adaptive convolutional sparsity with sub-band correlation in the NSCT domain for MRI image fusion Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-26 Qiu Hu, Weiming Cai, Shuwen Xu, Shaohai Hu, Lang Wang, Xinyi He
Objective. Multimodal medical image fusion (MMIF) technologies merges diverse medical images with rich information, boosting diagnostic efficiency and accuracy. Due to global optimization and single-valued nature, convolutional sparse representation (CSR) outshines the standard sparse representation (SR) in significance. By addressing the challenges of sensitivity to highly redundant dictionaries and
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Discrete residual diffusion model for high-resolution prostate MRI synthesis Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-26 Zhitao Han, Wenhui Huang
Objective. High-resolution magnetic resonance imaging (HR MRI) is an effective tool for diagnosing PCa, but it requires patients to remain immobile for extended periods, increasing chances of image distortion due to motion. One solution is to utilize super-resolution (SR) techniques to process low-resolution (LR) images and create a higher-resolution version. However, existing medical SR models suffer
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TdDS-UNet: top-down deeply supervised U-Net for the delineation of 3D colorectal cancer Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Shuchao Chen, Fei Xie, Shenghuan Chen, Shanshan Liu, Haojiang Li, Qiong Gong, Guangying Ruan, Lizhi Liu, Hongbo Chen
Automatically delineating colorectal cancers with fuzzy boundaries from 3D images is a challenging task, but the problem of fuzzy boundary delineation in existing deep learning-based methods have not been investigated in depth. Here, an encoder–decoder-based U-shaped network (U-Net) based on top-down deep supervision (TdDS) was designed to accurately and automatically delineate the fuzzy boundaries
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Impact of and interplay between proton arc therapy and range uncertainties in proton therapy for head-and-neck cancer Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Sebastian Tattenberg, Peilin Liu, Anthony Mulhem, Xiaoda Cong, Christopher Thome, Xuanfeng Ding
Objective. Proton therapy reduces the integral dose to the patient compared to conventional photon treatments. However, in vivo proton range uncertainties remain a considerable hurdle. Range uncertainty reduction benefits depend on clinical practices. During intensity-modulated proton therapy (IMPT), the target is irradiated from only a few directions, but proton arc therapy (PAT), for which the target
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Semi-supervised low-dose SPECT restoration using sinogram inner-structure aware graph neural network Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Si Li, Keming Chen, Xiangyuan Ma, Zengguo Liang
Objective. To mitigate the potential radiation risk, low-dose single photon emission computed tomography (SPECT) is of increasing interest. Numerous deep learning-based methods have been developed to perform low-dose imaging while maintaining image quality. However, most existing methods seldom explore the unique inner-structure inherent within sinograms. In addition, traditional supervised learning
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Automated classification of ulcerative lesions in small intestine using densenet with channel attention and residual dilated blocks Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Xudong Guo, Lei Xu, Zhang Liu, Youguo Hao, Peng Wang, Huiyun Zhu, Yiqi Du
Objective. Ulceration of the small intestine, which has a high incidence, includes Crohn’s disease (CD), intestinal tuberculosis (ITB), primary small intestinal lymphoma (PSIL), cryptogenic multifocal ulcerous stenosing enteritis (CMUSE), and non-specific ulcer (NSU). However, the ulceration morphology can easily be misdiagnosed through enteroscopy. Approach. In this study, DRCA-DenseNet169, which
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Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Joseph B Mandeville, Nikos Efthimiou, Jonah Weigand-Whittier, Erin Hardy, Gitte M Knudsen, Louise M Jørgensen, Yin-Ching I Chen
Objective. Most methods for partial volume correction (PVC) of positron emission tomography (PET) data employ anatomical segmentation of images into regions of interest. This approach is not optimal for exploratory functional imaging beyond regional hypotheses. Here, we describe a novel method for unbiased voxel-wise PVC. Approach. B-spline basis functions were combined with geometric transfer matrices
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Setup and characterisation according to NEMA NU 4 of the phenoPET scanner, a PET system dedicated for plant sciences Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-23 Carsten Hinz, Siegfried Jahnke, Ralf Metzner, Daniel Pflugfelder, Jürgen Scheins, Matthias Streun, Robert Koller
Objective. The phenoPET system is a plant dedicated positron emission tomography (PET) scanner consisting of fully digital photo multipliers with lutetium–yttrium oxyorthosilicate crystals and located inside a custom climate chamber. Here, we present the setup of phenoPET, its data processing and image reconstruction together with its performance. Approach. The performance characterization follows
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A triple-imaging-modality system for simultaneous measurements of prompt gamma photons, prompt x-rays, and induced positrons during proton beam irradiation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-22 Seiichi Yamamoto, Hiroshi Watabe, Kohei Nakanishi, Takuya Yabe, Mitsutaka Yamaguchi, Naoki Kawachi, Kei Kamada, Akira Yoshikawa, Masayasu Miyake, Kazuo S Tanaka, Jun Kataoka
Objective. Prompt gamma photon, prompt x-ray, and induced positron imaging are possible methods for observing a proton beam’s shape from outside the subject. However, since these three types of images have not been measured simultaneously nor compared using the same subject, their advantages and disadvantages remain unknown for imaging beam shapes in therapy. To clarify these points, we developed a
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A novel predict method for muscular invasion of bladder cancer based on 3D mp-MRI feature fusion Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-22 Jie Yu, Lingkai Cai, Chunxiao Chen, Yuan Zou, Yueyue Xiao, Xue Fu, Liang Wang, Xiao Yang, Peikun Liu, Qiang Lu, Xueying Sun, Qiang Shao
Objective. To assist urologist and radiologist in the preoperative diagnosis of non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), we proposed a combination models strategy (CMS) utilizing multiparametric magnetic resonance imaging. Approach. The CMS includes three components: image registration, image segmentation, and multisequence feature fusion. To ensure spatial
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High-resolution EEG source localization in personalized segmentation-free head model with multi-dipole fitting Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-22 Akimasa Hirata, Masamune Niitsu, Chun Ren Phang, Sachiko Kodera, Tetsuo Kida, Essam A Rashed, Masaki Fukunaga, Norihiro Sadato, Toshiaki Wasaka
Objective. Electroencephalograms (EEGs) are often used to monitor brain activity. Several source localization methods have been proposed to estimate the location of brain activity corresponding to EEG readings. However, only a few studies evaluated source localization accuracy from measured EEG using personalized head models in a millimeter resolution. In this study, based on a volume conductor analysis
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Equivalent-time-active-cavitation-imaging enables vascular-resolution blood-brain-barrier-opening-therapy planning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-22 Samuel Desmarais, Gerardo Ramos-Palacios, Jonathan Porée, Stephen A Lee, Alexis Leconte, Abbas F Sadikot, Jean Provost
Objective. Linking cavitation and anatomy was found to be important for predictable outcomes in focused-ultrasound blood-brain-barrier-opening and requires high resolution cavitation mapping. However, cavitation mapping techniques for planning and monitoring of therapeutic procedures either (1) do not leverage the full resolution capabilities of ultrasound imaging or (2) place constraints on the length
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Mini-GRID radiotherapy on the CLEAR very-high-energy electron beamline: collimator optimization, film dosimetry, and Monte Carlo simulations Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Nathan Clements, Nolan Esplen, Joseph Bateman, Cameron Robertson, Manjit Dosanjh, Pierre Korysko, Wilfrid Farabolini, Roberto Corsini, Magdalena Bazalova-Carter
Objective. Spatially-fractionated radiotherapy (SFRT) delivered with a very-high-energy electron (VHEE) beam and a mini-GRID collimator was investigated to achieve synergistic normal tissue-sparing through spatial fractionation and the FLASH effect. Approach. A tungsten mini-GRID collimator for delivering VHEE SFRT was optimized using Monte Carlo (MC) simulations. Peak-to-valley dose ratios (PVDRs)
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Deep learning for head and neck semi-supervised semantic segmentation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Shunyao Luan, Yi Ding, Jiakang Shao, Bing Zou, Xiao Yu, Nannan Qin, Benpeng Zhu, Wei Wei, Xudong Xue
Objective. Radiation therapy (RT) represents a prevalent therapeutic modality for head and neck (H&N) cancer. A crucial phase in RT planning involves the precise delineation of organs-at-risks (OARs), employing computed tomography (CT) scans. Nevertheless, the manual delineation of OARs is a labor-intensive process, necessitating individual scrutiny of each CT image slice, not to mention that a standard
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Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Devon Richtsmeier, Pierre-Antoine Rodesch, Kris Iniewski, Magdalena Bazalova-Carter
Objective. Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident
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Energy painting: helium-beam radiography with thin detectors and multiple beam energies Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Margareta Metzner, Daria Zhevachevska, Annika Schlechter, Florian Kehrein, Julian Schlecker, Carlos Murillo, Stephan Brons, Oliver Jäkel, Mária Martišíková, Tim Gehrke
Objective. Compact ion imaging systems based on thin detectors are a promising prospect for the clinical environment since they are easily integrated into the clinical workflow. Their measurement principle is based on energy deposition instead of the conventionally measured residual energy or range. Therefore, thin detectors are limited in the water-equivalent thickness range they can image with high
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Experimental validation of absorbed dose-to-medium calculation algorithms in heterogeneous media Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Alexia Delbaere, Tony Younes, Catherine Khamphan, Laure Vieillevigne
Objective. The aim of this work was to determine heterogeneous correction factors hQclin,Qreffclin,frefdetm,w to validate absorbed dose-to-medium Dm,Qclinm,fclin calculation algorithms from detector readings. The impact of detector orientation perpendicular and parallel to the beam central axis on the correction factors was also investigated. Approach. The hQclin,Qreffclin,frefdetm,w factors were calculated
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How does the electric field induced by tDCS influence motor-related connectivity? Model-guided perspectives Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Sofia Rita Fernandes, M Amparo Callejón-Leblic, Hugo Alexandre Ferreira
Over the last decade, transcranial direct current stimulation (tDCS) has been applied not only to modulate local cortical activation, but also to address communication between functionally-related brain areas. Stimulation protocols based on simple two-electrode placements are being replaced by multi-electrode montages to target intra- and inter-hemispheric neural networks using multichannel/high definition
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Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Björn Eiben, Jenny Bertholet, Elena H Tran, Andreas Wetscherek, Anna-Maria Shiarli, Simeon Nill, Uwe Oelfke, Jamie R McClelland
Objective. Respiratory motion of lung tumours and adjacent structures is challenging for radiotherapy. Online MR-imaging cannot currently provide real-time volumetric information of the moving patient anatomy, therefore limiting precise dose delivery, delivered dose reconstruction, and downstream adaptation methods. Approach. We tailor a respiratory motion modelling framework towards an MR-Linac workflow
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MRI non-rigid registration with tumor contraction correction for ablative margin assessment after microwave ablation of hepatocellular carcinomas Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Li-nan Dong, Shouchao Wang, Guoping Dong, Dexing Kong, Ping Liang
Objective. This study aims to develop and assess a tumor contraction model, enhancing the precision of ablative margin (AM) evaluation after microwave ablation (MWA) treatment for hepatocellular carcinomas (HCCs). Approach. We utilize a probabilistic method called the coherent point drift algorithm to align pre-and post-ablation MRI images. Subsequently, a nonlinear regression method quantifies local
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A model-based direct inversion network (MDIN) for dual spectral computed tomography Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Haichuan Zhou, Huitao Zhang, Xing Zhao, Peng Zhang, Yining Zhu
Objective. Dual spectral computed tomography (DSCT) is a very challenging problem in the field of imaging. Due to the nonlinearity of its mathematical model, the images reconstructed by the conventional CT usually suffer from the beam hardening artifacts. Additionally, several existing DSCT methods rely heavily on the information of the spectra, which is often not readily available in applications
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Development and optimisation of grid inserts for a preclinical radiotherapy system and corresponding Monte Carlo beam simulations Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-19 Marcus Fisk, Pejman Rowshanfarzad, David Pfefferlé, Matthew Fernandez de Viana, Julian Cabrera, Martin A Ebert
Objective. To develop a physical grid collimator compatible with the X-RAD preclinical radiotherapy system and create a corresponding Monte Carlo (MC) model. Approach. This work presents a methodology for the fabrication of a grid collimator designed for utilisation on the X-RAD preclinical radiotherapy system. Additionally, a MC simulation of the grid is developed, which is compatible with the X-RAD
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Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-16 Reimund Bayerlein, Benjamin A Spencer, Edwin K Leung, Negar Omidvari, Yasser G Abdelhafez, Qian Wang, Lorenzo Nardo, Simon R Cherry, Ramsey D Badawi
Objective. This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner. Approach. Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode
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Sacroiliitis diagnosis based on interpretable features and multi-task learning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-16 Lei Liu, Haoyu Zhang, Weifeng Zhang, Wei Mei, Ruibin Huang
Objective. Sacroiliitis is an early pathological manifestation of ankylosing spondylitis (AS), and a positive sacroiliitis test on imaging may help clinical practitioners diagnose AS early. Deep learning based automatic diagnosis algorithms can deliver grading findings for sacroiliitis, however, it requires a large amount of data with precise labels to train the model and lacks grading features visualization
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Radiological injuries under low energy x-rays in mice depending on dose and protocol: comparative characterization of lesion severity and impact of the in vivo bone response on retrospective dose estimations Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-16 Manon Guillou, Bruno L’Homme, François Trompier, Anass Errabii, Tifanie Marcoux, Gaëtan Gruel, Yolanda Prezado, Morgane Dos Santos
Objective. To improve our knowledge about the biological effects of over exposures involving low-energy x-rays, we developed and characterized a preclinical mouse model allowing to mimic different lesion severity degrees induced by 80 kV x-ray depending on the dose and protocol (single or repeated exposure). Approach. Mice were locally exposed (paw) to 80 kV x-rays in a single (15, 30 or 45 Gy in K
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A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-15 Lijun Bao, Hongyuan Zhang, Zeyu Liao
Objective. Quantitative susceptibility mapping (QSM) is a new imaging technique for non-invasive characterization of the composition and microstructure of in vivo tissues, and it can be reconstructed from local field measurements by solving an ill-posed inverse problem. Even for deep learning networks, it is not an easy task to establish an accurate quantitative mapping between two physical quantities
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A simulation study on the radiosensitization properties of gold nanorods Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-15 Ali Taheri, Mayeen Uddin Khandaker, Farhad Moradi, David Andrew Bradley
Objective. Gold nanorods (GNRs) have emerged as versatile nanoparticles with unique properties, holding promise in various modalities of cancer treatment through drug delivery and photothermal therapy. In the rapidly evolving field of nanoparticle radiosensitization (NPRS) for cancer therapy, this study assessed the potential of gold nanorods as radiosensitizing agents by quantifying the key features
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Attenuation correction and truncation completion for breast PET/MR imaging using deep learning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-15 Xue Li, Jacob M Johnson, Roberta M Strigel, Leah C Henze Bancroft, Samuel A Hurley, S Iman Zare Estakhraji, Manoj Kumar, Amy M Fowler, Alan B McMillan
Objective. Simultaneous PET/MR scanners combine the high sensitivity of MR imaging with the functional imaging of PET. However, attenuation correction of breast PET/MR imaging is technically challenging. The purpose of this study is to establish a robust attenuation correction algorithm for breast PET/MR images that relies on deep learning (DL) to recreate the missing portions of the patient’s anatomy
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Balanced transformer: efficient classification of glioblastoma and primary central nervous system lymphoma Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-15 Shigang Wang, Jinyang Wu, Meimei Chen, Sa Huang, Qian Huang
Objective. Primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) are malignant primary brain tumors with different biological characteristics. Great differences exist between the treatment strategies of PCNSL and GBM. Thus, accurately distinguishing between PCNSL and GBM before surgery is very important for guiding neurosurgery. At present, the spinal fluid of patients is commonly
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Virtual dosimetry study with three cone-beam breast computed tomography scanners using a fast GPU-based Monte Carlo code Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-14 Giovanni Mettivier, Youfang Lai, Xun Jia, Paolo Russo
Objective. To compare the dosimetric performance of three cone-beam breast computed tomography (BCT) scanners, using real-time Monte Carlo-based dose estimates obtained with the virtual clinical trials (VCT)-BREAST graphical processing unit (GPU)-accelerated platform dedicated to VCT in breast imaging. Approach. A GPU-based Monte Carlo (MC) code was developed for replicating in silico the geometric
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Chest x-ray diagnosis via spatial-channel high-order attention representation learning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-13 Xinyue Gao, Bo Jiang, Xixi Wang, Lili Huang, Zhengzheng Tu
Objective. Chest x-ray image representation and learning is an important problem in computer-aided diagnostic area. Existing methods usually adopt CNN or Transformers for feature representation learning and focus on learning effective representations for chest x-ray images. Although good performance can be obtained, however, these works are still limited mainly due to the ignorance of mining the correlations
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Solving the MPI reconstruction problem with automatically tuned regularization parameters Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-13 Konrad Scheffler, Marija Boberg, Tobias Knopp
In the field of medical imaging, magnetic particle imaging (MPI) poses a promising non-ionizing tomographic technique with high spatial and temporal resolution. In MPI, iterative solvers are used to reconstruct the particle distribution out of the measured voltage signal based on a system matrix. The amount of regularization needed to reconstruct an image of good quality differs from measurement to
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Scintillation and cherenkov photon counting detectors with analog silicon photomultipliers for TOF-PET Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-13 Joshua W Cates, Woon-Seng Choong, Erik Brubaker
Objective. Standard signal processing approaches for scintillation detectors in positron emission tomography (PET) derive accurate estimates for 511 keV photon time of interaction and energy imparted to the detection media from aggregate characteristics of electronic pulse shapes. The ultimate realization of a scintillation detector for PET is one that provides a unique timestamp and position for each
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Evaluation of monte carlo to support commissioning of the treatment planning system of new pencil beam scanning proton therapy facilities Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-13 D Botnariuc, S Court, A Lourenço, A Gosling, G Royle, M Hussein, V Rompokos, C Veiga
ABSTRACT Objective. To demonstrate the potential of Monte Carlo (MC) to support the resource-intensive measurements that comprise the commissioning of the treatment planning system (TPS) of new proton therapy facilities. Approach. Beam models of a pencil beam scanning system (Varian ProBeam) were developed in GATE (v8.2), Eclipse proton convolution superposition algorithm (v16.1, Varian Medical Systems)
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UC-stack: a deep learning computer automatic detection system for diabetic retinopathy classification Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-12 Yong Fu, Yuekun Wei, Siying Chen, Caihong Chen, Rong Zhou, Hongjun Li, Mochan Qiu, Jin Xie, Daizheng Huang
Object. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system for the early detection and grading of DR, providing an automated alternative to the manual examination. Approach. First, we use advanced image preprocessing
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Assessment of valve regurgitation severity via contrastive learning and multi-view video integration Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-12 Sekeun Kim, Hui Ren, Jerome Charton, Jiang Hu, Carola A Maraboto Gonzalez, Jay Khambhati, Justin Cheng, Jeena DeFrancesco, Anam A Waheed, Sylwia Marciniak, Filipe Moura, Rhanderson N Cardoso, Bruno B Lima, Suzannah McKinney, Michael H Picard, Xiang Li, Quanzheng Li
Objective. This paper presents a novel approach for addressing the intricate task of diagnosing aortic valve regurgitation (AR), a valvular disease characterized by blood leakage due to incompetence of the valve closure. Conventional diagnostic techniques require detailed evaluations of multi-modal clinical data, frequently resulting in labor-intensive and time-consuming procedures that are vulnerable
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Pencil beam kernel-based dose calculations on CT data for a mixed neutron-gamma fission field applying tissue correction factors Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-12 Lucas B Sommer, Severin Kampfer, Tobias Chemnitz, Harald Breitkreutz, Stephanie E Combs, Jan J Wilkens
Objective. For fast neutron therapy with mixed neutron and gamma radiation at the fission neutron therapy facility MEDAPP at the research reactor FRM II in Garching, no clinical dose calculation software was available in the past. Here, we present a customized solution for research purposes to overcome this lack of three-dimensional dose calculation. Approach. The applied dose calculation method is
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A generalized model for monitor units determination in ocular proton therapy using machine learning: A proof-of-concept study Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-12 Emmanuelle Fleury, Joël Herault, Kees Spruijt, Jasper Kouwenberg, Gaëlle Angellier, Petter Hofverberg, Tomasz Horwacik, Tomasz Kajdrowicz, Jean-Philippe Pignol, Mischa Hoogeman, Petra Trnková
Objective. Determining and verifying the number of monitor units is crucial to achieving the desired dose distribution in radiotherapy and maintaining treatment efficacy. However, current commercial treatment planning system(s) dedicated to ocular passive eyelines in proton therapy do not provide the number of monitor units for patient-specific plan delivery. Performing specific pre-treatment field
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Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-09 David Viar-Hernández, Juan Antonio Vera-Sánchez, Lucia Schmidt-Santiago, Borja Rodriguez-Vila, Isabel Lorenzo-Villanueva, Elisabet Canals-de-las-Casas, Juan Castro-Novais, Juan Maria Perez-Moreno, Fernando Cerrón-Campoo, Norberto Malpica, Angel Torrado-Carvajal, Alejandro Mazal
We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation
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LA-Net: layer attention network for 3D-to-2D retinal vessel segmentation in OCTA images Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-09 Chaozhi Yang, Bei Li, Qian Xiao, Yun Bai, Yachuan Li, Zongmin Li, Hongyi Li, Hua Li
Objective. Retinal vessel segmentation from optical coherence tomography angiography (OCTA) volumes is significant in analyzing blood supply structures and the diagnosing ophthalmic diseases. However, accurate retinal vessel segmentation in 3D OCTA remains challenging due to the interference of choroidal blood flow signals and the variations in retinal vessel structure. Approach. This paper proposes
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In plane quantification of in vivo muscle elastic anisotropy factor by steered ultrasound pushing beams Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Ha-Hien-Phuong Ngo, Ricardo Andrade, Javier Brum, Nicolas Benech, Simon Chatelin, Aude Loumeaud, Thomas Frappart, Christophe Fraschini, Antoine Nordez, Jean-Luc Gennisson
Objective. Skeletal muscles are organized into distinct layers and exhibit anisotropic characteristics across various scales. Assessing the arrangement of skeletal muscles may provide valuable biomarkers for diagnosing muscle-related pathologies and evaluating the efficacy of clinical interventions. Approach. In this study, we propose a novel ultrafast ultrasound sequence constituted of steered pushing
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Development and tuning of models for accurate simulation of CT spatial resolution using CatSim Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Jiayong Zhang, Mingye Wu, Paul FitzGerald, Stephen Araujo, Bruno De Man
Objective. We sought to systematically evaluate CatSim’s ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically used x-ray techniques. Approach. Using a 64-detector-row clinical scanner, we scanned two phantoms designed to evaluate spatial resolution in the projection and image
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Quantum annealing-based computed tomography using variational approach for a real-number image reconstruction Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Akihiro Haga
Objective. Despite recent advancements in quantum computing, the limited number of available qubits has hindered progress in CT reconstruction. This study investigates the feasibility of utilizing quantum annealing-based computed tomography (QACT) with current quantum bit levels. Approach. The QACT algorithm aims to precisely solve quadratic unconstrained binary optimization problems. Furthermore,
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Toward quantitative intrafractional monitoring in paraspinal SBRT using a proprietary software application: clinical implementation and patient results Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Qiyong Fan, Hai Pham, Xiang Li, Pengpeng Zhang, Lei Zhang, Yabo Fu, Bohong Huang, Cindy Li, John Cuaron, Laura Cerviño, Jean M. Moran, Tianfang Li
Objective. We report on paraspinal motion and the clinical implementation of our proprietary software that leverages Varian’s intrafraction motion review (IMR) capability for quantitative tracking of the spine during paraspinal SBRT. The work is based on our prior development and analysis on phantoms. Approach. To address complexities in patient anatomy, digitally reconstructed radiographs (DRR’s)
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Quantitative pulsatility measurements using 3D dynamic ultrasound localization microscopy Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Chloé Bourquin, Jonathan Porée, Brice Rauby, Vincent Perrot, Nin Ghigo, Hatim Belgharbi, Samuel Bélanger, Gerardo Ramos-Palacios, Nelson Cortes, Hugo Ladret, Lamyae Ikan, Christian Casanova, Frédéric Lesage, Jean Provost
A rise in blood flow velocity variations (i.e. pulsatility) in the brain, caused by the stiffening of upstream arteries, is associated with cognitive impairment and neurodegenerative diseases. The study of this phenomenon requires brain-wide pulsatility measurements, with large penetration depth and high spatiotemporal resolution. The development of dynamic ultrasound localization microscopy (DULM)
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ACnerf: enhancement of neural radiance field by alignment and correction of pose to reconstruct new views from a single x-ray* * This work was supported in part by the Science and Technology Commission of Shanghai Municipality under Grant 20DZ2254400 and 20DZ2261200; in part by Shanghai Municipal Science and Technology Major Project under Grant ZD2021CY001. Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-08 Mengcheng Sun, Yu Zhu, Hangyu Li, Jiongyao Ye, Nan Li
Objective. Computed tomography (CT) is widely used in medical research and clinical diagnosis. However, acquiring CT data requires patients to be exposed to considerable ionizing radiance, leading to physical harm. Recent studies have considered using neural radiance field (NERF) techniques to infer the full-view CT projections from single-view x-ray projection, thus aiding physician judgment and reducing
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Reproducible spectral CT thermometry with liver-mimicking phantoms for image-guided thermal ablation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-05 Leening P Liu, Rizza Pua, Derick N Rosario-Berrios, Olivia F Sandvold, Amy E Perkins, David P Cormode, Nadav Shapira, Michael C Soulen, Peter B Noël
Objectives. Evaluate the reproducibility, temperature tolerance, and radiation dose requirements of spectral CT thermometry in tissue-mimicking phantoms to establish its utility for non-invasive temperature monitoring of thermal ablations. Methods. Three liver mimicking phantoms embedded with temperature sensors were individually scanned with a dual-layer spectral CT at different radiation dose levels
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Intensive vision-guided network for radiology report generation Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-05 Fudan Zheng, Mengfei Li, Ying Wang, Weijiang Yu, Ruixuan Wang, Zhiguang Chen, Nong Xiao, Yutong Lu
Objective. Automatic radiology report generation is booming due to its huge application potential for the healthcare industry. However, existing computer vision and natural language processing approaches to tackle this problem are limited in two aspects. First, when extracting image features, most of them neglect multi-view reasoning in vision and model single-view structure of medical images, such
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Effects of cellular radioresponse on therapeutic helium-, carbon-, oxygen-, and neon-ion beams: a simulation study Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-05 Takamitsu Masuda, Taku Inaniwa
Objective. Helium, oxygen, and neon ions in addition to carbon ions will be used for hypofractionated multi-ion therapy to maximize the therapeutic effectiveness of charged-particle therapy. To use new ions in cancer treatments based on the dose-fractionation protocols established in carbon-ion therapy, this study examined the cell-line-specific radioresponse to therapeutic helium-, oxygen-, and neon-ion
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Interactive segmentation of medical images using deep learning Phys. Med. Biol. (IF 3.5) Pub Date : 2024-02-05 Xiaoran Zhao, Haixia Pan, Wenpei Bai, Bin Li, Hongqiang Wang, Meng Zhang, Yanan Li, Dongdong Zhang, Haotian Geng, Minghuang Chen
Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount of labeled data. When performing pixel-level labeling on medical images, labeling a target requires marking ten or even hundreds of points along its edge, which requires a lot of time and labor costs. To reduce the labeling cost, we utilize a click-based