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Long-axial field-of-view PET/CT for the assessment of inflammation in calcified coronary artery plaques with [68 Ga]Ga-DOTA-TOC Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-23 Clemens Mingels, Hasan Sari, Nasir Gözlügöl, Carola Bregenzer, Luisa Knappe, Korbinian Krieger, Ali Afshar-Oromieh, Thomas Pyka, Lorenzo Nardo, Christoph Gräni, Ian Alberts, Axel Rominger, Federico Caobelli
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The prognostic significance of a negative PSMA-PET scan prior to salvage radiotherapy following radical prostatectomy Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-22 Sonja Adebahr, Alexander Althaus, Sophia Scharl, Iosif Strouthos, Andrea Farolfi, Francesca Serani, Helena Lanzafame, Christian Trapp, Stefan A. Koerber, Jan C. Peeken, Marco M. E. Vogel, Alexis Vrachimis, Simon K. B. Spohn, Anca-Ligia Grosu, Stephanie G. C. Kroeze, Matthias Guckenberger, Stefano Fanti, George Hruby, Louise Emmett, Claus Belka, Nina-Sophie Schmidt-Hegemann, Christoph Henkenberens,
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Learning joint surface reconstruction and segmentation, from brain images to cortical surface parcellation Med. Image Anal. (IF 10.9) Pub Date : 2023-09-22 Karthik Gopinath, Christian Desrosiers, Herve Lombaert
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Backdoor attack and defense in federated generative adversarial network-based medical image synthesis Med. Image Anal. (IF 10.9) Pub Date : 2023-09-22 Ruinan Jin, Xiaoxiao Li
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Distinct subtypes of spatial brain metabolism patterns in Alzheimer’s disease identified by deep learning-based FDG PET clusters Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-22 Hyun Gee Ryoo, Hongyoon Choi, Kuangyu Shi, Axel Rominger, Dong Young Lee, Dong Soo Lee
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Patterns of PET-positive residual tissue at interim restaging and risk of treatment failure in advanced-stage Hodgkin’s lymphoma: an analysis of the randomized phase III HD18 trial by the German Hodgkin Study Group Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-22 Justin Ferdinandus, Lutz van Heek, Katrin Roth, Markus Dietlein, Hans-Theodor Eich, Christian Baues, Peter Borchmann, Carsten Kobe
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Validation of the ΔSUVmax for Interim PET Interpretation in Diffuse Large B-Cell Lymphoma on the Basis of the GAINED Clinical Trial J Nucl. Med. (IF 9.3) Pub Date : 2023-09-21 Emmanuel Itti, Paul Blanc-Durand, Alina Berriolo-Riedinger, Salim Kanoun, Françoise Kraeber-Bodéré, Michel Meignan, Elodie Gat, Steven Le Gouill, René-Olivier Casasnovas, Caroline Bodet-Milin
The GAINED phase 3 trial (ClinicalTrials.gov identifier: NCT01659099) evaluated a PET-driven consolidative strategy in patients with diffuse large B-cell lymphoma. In this post hoc analysis, we aimed to compare the prognostic value of the per-protocol PET interpretation criteria (Menton 2011 consensus) with the change in the SUVmax (ΔSUVmax) alone. Methods: Real-time central review of 18F-FDG PET/CT
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Antihormonal-Treatment Status Affects 68Ga-PSMA-HBED-CC PET Biodistribution in Patients with Prostate Cancer J Nucl. Med. (IF 9.3) Pub Date : 2023-09-21 Kilian Kluge, David Haberl, Holger Einspieler, Sazan Rasul, Sebastian Gutschmayer, Lukas Kenner, Gero Kramer, Bernhard Grubmüller, Shahrokh Shariat, Alexander Haug, Marcus Hacker
Androgen deprivation therapy (ADT) is known to influence the prostate-specific membrane antigen (PSMA) expression of prostate cancer, potentially complicating the interpretation of PSMA ligand PET findings and affecting PSMA radioligand therapy. However, the impact of ADT on PSMA ligand biodistribution in nontumorous organs is not well understood. Methods: Men (n = 112) with histologically proven prostate
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Oncologic Staging with 68Ga-FAPI PET/CT Demonstrates a Lower Rate of Nonspecific Lymph Node Findings Than 18F-FDG PET/CT J Nucl. Med. (IF 9.3) Pub Date : 2023-09-21 Tristan T. Demmert, Kelsey L. Pomykala, Helena Lanzafame, Kim M. Pabst, Katharina Lueckerath, Jens Siveke, Lale Umutlu, Hubertus Hautzel, Rainer Hamacher, Ken Herrmann, Wolfgang P. Fendler
Nonspecific lymph node uptake on 18F-FDG PET/CT imaging is a significant pitfall for tumor staging. Fibroblast activation protein α expression on cancer-associated fibroblasts and some tumor cells is less sensitive to acute inflammatory stimuli, and fibroblast activation protein–directed PET may overcome this limitation. Methods: Eighteen patients from our prospective observational study underwent
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Tumor-Targeted Interleukin 2 Boosts the Anticancer Activity of FAP-Directed Radioligand Therapeutics J Nucl. Med. (IF 9.3) Pub Date : 2023-09-21 Galbiati, A., Dorten, P., Gilardoni, E., Gierse, F., Bocci, M., Zana, A., Mock, J., Claesener, M., Cufe, J., Buther, F., Schafers, K., Hermann, S., Schafers, M., Neri, D., Cazzamalli, S., Backhaus, P.
Visual Abstract
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GAMMA challenge: Glaucoma grAding from Multi-Modality imAges Med. Image Anal. (IF 10.9) Pub Date : 2023-09-18 Junde Wu, Huihui Fang, Fei Li, Huazhu Fu, Fengbin Lin, Jiongcheng Li, Yue Huang, Qinji Yu, Sifan Song, Xinxing Xu, Yanyu Xu, Wensai Wang, Lingxiao Wang, Shuai Lu, Huiqi Li, Shihua Huang, Zhichao Lu, Chubin Ou, Xifei Wei, Bingyuan Liu, Yanwu Xu
Glaucoma is a chronic neuro-degenerative condition that is one of the world’s leading causes of irreversible but preventable blindness. The blindness is generally caused by the lack of timely detection and treatment. Early screening is thus essential for early treatment to preserve vision and maintain life quality. Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective
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A deep weakly semi-supervised framework for endoscopic lesion segmentation Med. Image Anal. (IF 10.9) Pub Date : 2023-09-20 Yuxuan Shi, Hong Wang, Haoqin Ji, Haozhe Liu, Yuexiang Li, Nanjun He, Dong Wei, Yawen Huang, Qi Dai, Jianrong Wu, Xinrong Chen, Yefeng Zheng, Hongmeng Yu
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Dynamic feature splicing for few-shot rare disease diagnosis Med. Image Anal. (IF 10.9) Pub Date : 2023-09-16 Yuanyuan Chen, Xiaoqing Guo, Yongsheng Pan, Yong Xia, Yixuan Yuan
Annotated images for rare disease diagnosis are extremely hard to collect. Therefore, identifying rare diseases under a few-shot learning (FSL) setting is significant. Existing FSL methods transfer useful and global knowledge from base classes with abundant training samples to enrich features of novel classes with few training samples, but still face difficulties when being applied to medical images
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Shear-Wave Elastography Reflects Myocardial Stiffness Changes in Pediatric Inflammatory Syndrome Post COVID-19 JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-20 Ahmed S. Youssef, Thomas Salaets, Stéphanie Bézy, Laurine Wouters, Marta Orlowska, Annette Caenen, Jürgen Duchenne, Alexis Puvrez, Lien De Somer, Bjorn Cools, Jan D’hooge, Marc Gewillig, Jens-Uwe Voigt
Abstract not available
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Comparison Between Acoustic Radiation Force-Induced and Natural Wave Velocities for Myocardial Stiffness Assessment in Hypertrophic Cardiomyopathy JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-20 Aimen Malik, Jose Carlos Villalobos Lizardi, Jerome Baranger, Maelys Venet, Mathieu Pernot, Seema Mital, Minh Bao Nguyen, Rajiv Chaturvedi, Luc Mertens, Olivier Villemain
Abstract not available
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Tricuspid Regurgitation: From imaging to clinical trials to resolving the unmet need for treatment JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-20 Julia Grapsa, Fabien Praz, Paul Sorajja, Joao L. Cavalcante, Marta Sitges, Maurizio Taramasso, Nicolo Piazza, David Messika Zeitoun, Hector I. Michelena, Nadira Hamid, Julien Dreyfus, Giovanni Benfari, Edgar Argulian, Alaide Chieffo, Didier Tchetche, Lawrence Rudski, Jeroen J. Bax, Stephan Von Bardeleben, Tiffany Patterson, Simon Redwood, Maurice Enriquez Sarano
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PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-19 Yifan Zhong, Chuang Cai, Tao Chen, Hao Gui, Cheng Chen, Jiajun Deng, Minglei Yang, Bentong Yu, Yongxiang Song, Tingting Wang, Yangchun Chen, Huazheng Shi, Dong Xie, Chang Chen, Yunlang She
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[68Ga]Ga‑LNC1007 PET/CT in the evaluation of renal cell carcinoma: comparison with 2-[18F]FDG/[68Ga]Ga-PSMA PET/CT Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-20 Rong Lin, Chao Wang, Shaohao Chen, Tingting Lin, Hai Cai, Shaoming Chen, Yun Yang, Jiaying Zhang, Fuqi Xu, Jingjing Zhang, Xiaoyuan Chen, Jie Zang, Weibing Miao
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Analysis of image data from the EuroNet PHL-C2 trial indicates a potential reduction in injected F-18 FDG activities in children: a proposal to update the EANM Paediatric Dosage Card Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-20 Johannes Tran-Gia, Uta Eberlein, Michael Lassmann, Christine Mauz-Körholz, Dieter Körholz, Pietro Zuccetta, Zvi Bar-Sever, Ute Rosner, Thomas Walter Georgi, Osama Sabri, Regine Kluge, Arnoldo Piccardo, Lars Kurch
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Baseline [18F]FDG PET features are associated with survival and toxicity in patients treated with CAR T cells for large B cell lymphoma Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-18 E. Marchal, X. Palard-Novello, F. Lhomme, M. E. Meyer, G. Manson, A. Devillers, J. P. Marolleau, R. Houot, A. Girard
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A phase I/II study of the safety and efficacy of [177Lu]Lu-satoreotide tetraxetan in advanced somatostatin receptor-positive neuroendocrine tumours Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-18 Damian Wild, Henning Grønbæk, Shaunak Navalkissoor, Alexander Haug, Guillaume P. Nicolas, Ben Pais, Catherine Ansquer, Jean-Mathieu Beauregard, Alexander McEwan, Michael Lassmann, Daniele Pennestri, Magali Volteau, Nat P. Lenzo, Rodney J. Hicks
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Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge Med. Image Anal. (IF 10.9) Pub Date : 2023-09-18 Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Olena Tankyevych, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, Adrien Depeursinge
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Improved diagnostic accuracy for coronary artery disease detection with quantitative 3D 82Rb PET myocardial perfusion imaging Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-18 Jennifer M. Renaud, Alexis Poitrasson-Rivière, Jonathan B. Moody, Tomoe Hagio, Edward P. Ficaro, Venkatesh L. Murthy
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Latent Transformer Models for out-of-distribution detection Med. Image Anal. (IF 10.9) Pub Date : 2023-09-16 Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Petteri Teikari, Ashay Patel, Jean-Marie U-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso
Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One popular approach to this challenge is to develop predictive models that can provide a measure of their uncertainty. Another approach is to use generative modelling to quantify the likelihood of inputs. Inputs with a low enough likelihood are deemed to be out-of-distribution and
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Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke Med. Image Anal. (IF 10.9) Pub Date : 2023-09-15 Lucas de Vries, Rudolf L.M. van Herten, Jan W. Hoving, Ivana Išgum, Bart J. Emmer, Charles B.L.M. Majoie, Henk A. Marquering, Efstratios Gavves
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One-shot segmentation of novel white matter tracts via extensive data augmentation and adaptive knowledge transfer Med. Image Anal. (IF 10.9) Pub Date : 2023-09-15 Wan Liu, Zhizheng Zhuo, Yaou Liu, Chuyang Ye
The use of convolutional neural networks (CNNs) has allowed accurate white matter (WM) tract segmentation on diffusion magnetic resonance imaging (dMRI). To train the CNN-based segmentation models, a large number of scans on which WM tracts are annotated need to be collected, and these annotated scans can be accumulated over a long period of time. However, when novel WM tracts that are different from
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Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography Med. Image Anal. (IF 10.9) Pub Date : 2023-09-15 Yi Gu, Yoshito Otake, Keisuke Uemura, Mazen Soufi, Masaki Takao, Hugues Talbot, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato
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Melanin-targeted [18F]-PFPN PET imaging may shed light for clear cell sarcoma Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-16 Xiao Zhang, Fei Kang, Huaiyuan Zheng, Yongkang Gai, Jing Wang, Xiaoli Lan
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Possible Causes and Clinical Relevance of a “Ring-Like” Late Gadolinium Enhancement Pattern JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-13 Michael Bietenbeck, Claudia Meier, Dennis Korthals, Maria Theofanidou, Philipp Stalling, Sven Dittmann, Eric Schulze-Bahr, Lars Eckardt, Ali Yilmaz
Abstract not available
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[177Lu]Lu-PSMA-617 Versus Docetaxel in Chemotherapy-Naïve Metastatic Castration-Resistant Prostate Cancer: Final Survival Analysis of a Phase 2 Randomized, Controlled Trial J Nucl. Med. (IF 9.3) Pub Date : 2023-09-14 Swayamjeet Satapathy, Bhagwant Rai Mittal, Ashwani Sood, Chandan Krushna Das, Ravimohan Suryanarayan Mavuduru, Shikha Goyal, Jaya Shukla, Shrawan Kumar Singh
The prostate-specific membrane antigen (PSMA) inhibitor [177Lu]Lu-PSMA-617 has been previously demonstrated to be noninferior to docetaxel in achieving a biochemical response in chemotherapy-naïve metastatic castration-resistant prostate cancer patients. Here, we report the final analysis of overall survival (OS) for a phase 2 randomized, controlled trial. Methods: Forty chemotherapy-naïve, PSMA-positive
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ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports? J Nucl. Med. (IF 9.3) Pub Date : 2023-09-14 Julian M.M. Rogasch, Giulia Metzger, Martina Preisler, Markus Galler, Felix Thiele, Winfried Brenner, Felix Feldhaus, Christoph Wetz, Holger Amthauer, Christian Furth, Imke Schatka
Visual Abstract
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Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework Med. Image Anal. (IF 10.9) Pub Date : 2023-09-14 Zong Fan, Ping Gong, Shanshan Tang, Christine U. Lee, Xiaohui Zhang, Pengfei Song, Shigao Chen, Hua Li
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A robust and interpretable deep learning framework for multi-modal registration via keypoints Med. Image Anal. (IF 10.9) Pub Date : 2023-09-13 Alan Q. Wang, Evan M. Yu, Adrian V. Dalca, Mert R. Sabuncu
We present KeyMorph, a deep learning-based image registration framework that relies on automatically detecting corresponding keypoints. State-of-the-art deep learning methods for registration often are not robust to large misalignments, are not interpretable, and do not incorporate the symmetries of the problem. In addition, most models produce only a single prediction at test-time. Our core insight
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Tumor radiogenomics in gliomas with Bayesian layered variable selection Med. Image Anal. (IF 10.9) Pub Date : 2023-09-12 Shariq Mohammed, Sebastian Kurtek, Karthik Bharath, Arvind Rao, Veerabhadran Baladandayuthapani
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Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation Med. Image Anal. (IF 10.9) Pub Date : 2023-09-12 Hyojoon Park, Bin Li, Yuming Liu, Michael S. Nelson, Helen M. Wilson, Eftychios Sifakis, Kevin W. Eliceiri
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The role of noise in denoising models for anomaly detection in medical images Med. Image Anal. (IF 10.9) Pub Date : 2023-09-11 Antanas Kascenas, Pedro Sanchez, Patrick Schrempf, Chaoyang Wang, William Clackett, Shadia S. Mikhael, Jeremy P. Voisey, Keith Goatman, Alexander Weir, Nicolas Pugeault, Sotirios A. Tsaftaris, Alison Q. O’Neil
Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are difficult to acquire. Therefore, unsupervised anomaly detection approaches have been proposed using only normal data for training, with the aim of detecting outlier anomalous voxels at test time. Denoising methods, for instance
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Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images Med. Image Anal. (IF 10.9) Pub Date : 2023-09-09 Ricardo Pizarro, Haz-Edine Assemlal, Sethu K. Boopathy Jegathambal, Thomas Jubault, Samson Antel, Douglas Arnold, Amir Shmuel
Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers
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A generic fundus image enhancement network boosted by frequency self-supervised representation learning Med. Image Anal. (IF 10.9) Pub Date : 2023-09-09 Heng Li, Haofeng Liu, Huazhu Fu, Yanwu Xu, Hai Shu, Ke Niu, Yan Hu, Jiang Liu
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Multi-site, Multi-domain Airway Tree Modeling Med. Image Anal. (IF 10.9) Pub Date : 2023-09-09 Minghui Zhang, Yangqian Wu, Hanxiao Zhang, Yulei Qin, Hao Zheng, Wen Tang, Corey Arnold, Chenhao Pei, Pengxin Yu, Yang Nan, Guang Yang, Simon Walsh, Dominic C. Marshall, Matthieu Komorowski, Puyang Wang, Dazhou Guo, Dakai Jin, Ya’nan Wu, Shuiqing Zhao, Runsheng Chang, Yun Gu
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT’09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven
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Heart and Brain Changes in Acute Coronary Syndromes (ACS) JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-13 Matthew G.L. Williams, Ngoc Jade Thai, Kate Liang, Estefania De Garate, Ronald Hartley-Davies, Christopher Lawton, Christelle Langley, Elanor C. Hinton, Chiara Bucciarelli-Ducci
Abstract not available
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Artificial Intelligence-Based Quantitative Coronary Plaque Analysis JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-13 Jacek Kwiecinski
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High-Risk Plaques on Coronary Computed Tomography Angiography: Correlation With Optical Coherence Tomography JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-13 Daisuke Kinoshita, Keishi Suzuki, Eisuke Usui, Masahiro Hada, Haruhito Yuki, Takayuki Niida, Yoshiyasu Minami, Hang Lee, Iris McNulty, Junya Ako, Maros Ferencik, Tsunekazu Kakuta, Ik-Kyung Jang
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Differences in whole-brain metabolism are associated with the expression of genes related to neurovascular unit integrity and synaptic plasticity in temporal lobe epilepsy Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-14 Ling Xiao, Yongxiang Tang, Chijun Deng, Jian Li, Rong Li, Haoyue Zhu, Danni Guo, Zhiquan Yang, Hongyu Long, Li Feng, Shuo Hu
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The feasibility of quantitative assessment of dynamic 18F-fluorodeoxyglucose PET in Takayasu’s arteritis: a pilot study Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-11 Yanhua Duan, Keyu Zan, Minjie Zhao, Yee Ling Ng, Hui Li, Min Ge, Leiying Chai, Xiao Cui, Wenjin Quan, Kun Li, Yun Zhou, Li Chen, Ximing Wang, Zhaoping Cheng
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Direct comparison and reproducibility of two segmentation methods for multicompartment dosimetry: round robin study on radioembolization treatment planning in hepatocellular carcinoma Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-12 Marnix Lam, Etienne Garin, Xavier Palard-Novello, Armeen Mahvash, Cheenu Kappadath, Paul Haste, Mark Tann, Ken Herrmann, Francesco Barbato, Brian Geller, Niklaus Schaefer, Alban Denys, Matthew Dreher, Kirk D. Fowers, Vanessa Gates, Riad Salem
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The potential role of osteoporosis in unspecific [18F]PSMA-1007 bone uptake Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-12 Gaia Ninatti, Cristiano Pini, Fabrizia Gelardi, Samuele Ghezzo, Paola Mapelli, Maria Picchio, Lidija Antunovic, Alberto Briganti, Francesco Montorsi, Claudio Landoni, Martina Sollini, Arturo Chiti
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How to attract young talent to nuclear medicine step 1: a survey conducted by the EANM Oncology and Theranostics Committee to understand the expectations of the next generation Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-09 Valentina Ambrosini, Sofia Carrilho Vaz, Niloefar Ahmadi Bidakhvidi, Marion Chanchou, Matthijs C. F. Cysouw, Francesca Serani, Conrad-Amadeus Voltin, Francoise Kraeber-Bodere, Christophe M. Deroose, Lioe-Fee De Geus-Oei, Matthias Eiber, Gopinath Gnanasegaran, Martin Gotthardt, Carsten Kobe, Mark W. Konijnenberg, Cristina Nanni, Daniela E. Oprea Lager, Kambiz Rahbar, David Taieb, Felix M. Mottaghy,
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Active learning for medical image segmentation with stochastic batches Med. Image Anal. (IF 10.9) Pub Date : 2023-09-12 Mélanie Gaillochet, Christian Desrosiers, Hervé Lombaert
The performance of learning-based algorithms improves with the amount of labelled data used for training. Yet, manually annotating data is particularly difficult for medical image segmentation tasks because of the limited expert availability and intensive manual effort required. To reduce manual labelling, active learning (AL) targets the most informative samples from the unlabelled set to annotate
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Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-08 Isaac Shiri, Yazdan Salimi, Mehdi Maghsudi, Elnaz Jenabi, Sara Harsini, Behrooz Razeghi, Shayan Mostafaei, Ghasem Hajianfar, Amirhossein Sanaat, Esmail Jafari, Rezvan Samimi, Maziar Khateri, Peyman Sheikhzadeh, Parham Geramifar, Habibollah Dadgar, Ahmad Bitrafan Rajabi, Majid Assadi, François Bénard, Alireza Vafaei Sadr, Slava Voloshynovskiy, Ismini Mainta, Carlos Uribe, Arman Rahmim, Habib Zaidi
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Prognostic Value of End-of-Treatment PSMA PET/CT in Patients Treated with 177Lu-PSMA Radioligand Therapy: A Retrospective, Single-Center Analysis J Nucl. Med. (IF 9.3) Pub Date : 2023-09-07 Vishnu Murthy, Andrei Gafita, Pan Thin, Kathleen Nguyen, Tristan Grogan, John Shen, Alexandra Drakaki, Matthew Rettig, Johannes Czernin, Jeremie Calais
Our objective was to evaluate the prognostic value of end-of-treatment prostate-specific membrane antigen (PSMA) PET/CT (PSMA-PET) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA radioligand therapy (PSMA-RLT). Methods: This was a single-center retrospective study. mCRPC patients who underwent PSMA-RLT with available baseline PSMA-PET (bPET) and end-of-treatment
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Improved Quality of Life in Metastatic Castration-Resistant Prostate Cancer Patients Receiving Consecutive Cycles of 177Lu-PSMA I&T J Nucl. Med. (IF 9.3) Pub Date : 2023-09-07 Amir Karimzadeh, Paula Soeiro, Benedikt Feuerecker, Charlotte-Sophie Hecker, Karina Knorr, Matthias M. Heck, Robert Tauber, Calogero D’Alessandria, Wolfgang A. Weber, Matthias Eiber, Isabel Rauscher
The aim of this retrospective analysis was to evaluate health-related quality of life (HRQoL) for patients with metastatic castration-resistant prostate cancer (mCRPC) receiving consecutive cycles of 177Lu-prostate-specific membrane antigen (PSMA) radioligand therapy (RLT) using the reliable and validated European Organization for Research and Treatment of Cancer core quality-of-life (QoL) questionnaire
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Impact of 68Ga-FAPI PET/CT on Staging and Oncologic Management in a Cohort of 226 Patients with Various Cancers J Nucl. Med. (IF 9.3) Pub Date : 2023-09-07 Stefan A. Koerber, Manuel Röhrich, Leon Walkenbach, Jakob Liermann, Peter L. Choyke, Christoph Fink, Cathrin Schroeter, Anna-Maria Spektor, Klaus Herfarth, Thomas Walle, Jeremie Calais, Hans-Ulrich Kauczor, Dirk Jaeger, Juergen Debus, Uwe Haberkorn, Frederik L. Giesel
Visual Abstract
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A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images Med. Image Anal. (IF 10.9) Pub Date : 2023-09-06 Xiaowei Xu, Qianjun Jia, Haiyun Yuan, Hailong Qiu, Yuhao Dong, Wen Xie, Zeyang Yao, Jiawei Zhang, Zhiqaing Nie, Xiaomeng Li, Yiyu Shi, James Y. Zou, Meiping Huang, Jian Zhuang
Congenital heart disease (CHD) is the most common type of birth defect. Without timely detection and treatment, approximately one-third of children with CHD would die in the infant period. However, due to the complicated heart structures, early diagnosis of CHD and its types is quite challenging, even for experienced radiologists. Here, we present an artificial intelligence (AI) system that achieves
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Translating Complex Machine-Learning Phenogrouping Into Simple Algorithm: Atrium, Ventricle, and Fibrosis in Mitral Valve Prolapse JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-06 Nobuyuki Kagiyama
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The value of bone SPECT/CT in evaluation of foot and ankle arthrodesis and adjacent joint secondary osteoarthritis Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-07 Ujwal Bhure, Hannes Grünig, Maria del Sol Pérez Lago, Dirk Lehnick, Martin Wonerow, Thiago Lima, Thomas F. Hany, Klaus Strobel
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New thresholds in semi-quantitative [18F]FDG PET/CT are needed to assess large vessel vasculitis with long-axial field-of-view scanners Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-07 Luisa Knappe, Carola Bregenzer, Nasir Gözlügöl, Clemens Mingels, Ian Alberts, Axel Rominger, Federico Caobelli
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The usefulness of [68 Ga]Ga-DOTA-JR11 PET/CT in patients with meningioma: comparison with MRI Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-08 Peipei Wang, Shuai Liu, Xiaojie Li, Xing Liu, Shaowu Li, Zhen Wu, Xin Cheng
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The True Power of Zero JACC Cardiovasc. Imaging (IF 14.0) Pub Date : 2023-09-04 Matthew J. Budoff
Abstract not available
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Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning Eur. J. Nucl. Med. Mol. Imaging (IF 9.1) Pub Date : 2023-09-06 Zhenxing Huang, Wenbo Li, Yaping Wu, Nannan Guo, Lin Yang, Na Zhang, Zhifeng Pang, Yongfeng Yang, Yun Zhou, Yue Shang, Hairong Zheng, Dong Liang, Meiyun Wang, Zhanli Hu
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Colonoscopy 3D video dataset with paired depth from 2D-3D registration Med. Image Anal. (IF 10.9) Pub Date : 2023-09-07 Taylor L. Bobrow, Mayank Golhar, Rohan Vijayan, Venkata S. Akshintala, Juan R. Garcia, Nicholas J. Durr