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Differential Diagnosis of Diabetic Foot Osteomyelitis and Charcot Neuropathic Osteoarthropathy with Deep Learning Methods J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-15 Maide Cakir, Gökalp Tulum, Ferhat Cuce, Kerim Bora Yilmaz, Ayse Aralasmak, Muhammet İkbal Isik, Hüseyin Canbolat
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An AI-Based Low-Risk Lung Health Image Visualization Framework Using LR-ULDCT J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-15 Swati Rai, Jignesh S. Bhatt, Sarat Kumar Patra
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An Exploratory Pilot Study on the Application of Radiofrequency Ablation for Atrial Fibrillation Guided by Computed Tomography-Based 3D Printing Technology J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-15
Abstract Radiofrequency ablation (RFA) is the treatment of choice for atrial fibrillation (AF). Additionally, the utilization of 3D printing for cardiac models offers an in-depth insight into cardiac anatomy and cardiovascular diseases. The study aims to evaluate the clinical utility and outcomes of RFA following in vitro visualization of the left atrium (LA) and pulmonary vein (PV) structures via
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Accuracy Analysis of 3D Bone Fracture Models: Effects of Computed Tomography (CT) Imaging and Image Segmentation J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-14 Martin Bittner-Frank, Andreas Strassl, Ewald Unger, Lena Hirtler, Barbara Eckhart, Markus Koenigshofer, Alexander Stoegner, Arastoo Nia, Domenik Popp, Franz Kainberger, Reinhard Windhager, Francesco Moscato, Emir Benca
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Checklist for Reproducibility of Deep Learning in Medical Imaging J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-14 Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile Safdar, Linda Moy, Felipe Kitamura, Amilcare Gentili, Paras Lakhani, Nina Kottler, Safwan S. Halabi, Joseph H. Yacoub, Yuankai Hou, Khaled Younis, Bradley J. Erickson, Elizabeth Krupinski, Shahriar Faghani
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A Data Augmentation Methodology to Reduce the Class Imbalance in Histopathology Images J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-14 Rodrigo Escobar Díaz Guerrero, Lina Carvalho, Thomas Bocklitz, Juergen Popp, José Luis Oliveira
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ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-14
Abstract Radiology narrative reports often describe characteristics of a patient’s disease, including its location, size, and shape. Motivated by the recent success of multimodal learning, we hypothesized that this descriptive text could guide medical image analysis algorithms. We proposed a novel vision-language model, ConTEXTual Net, for the task of pneumothorax segmentation on chest radiographs
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Adaptive Machine Learning Approach for Importance Evaluation of Multimodal Breast Cancer Radiomic Features J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-13 Giulio Del Corso, Danila Germanese, Claudia Caudai, Giada Anastasi, Paolo Belli, Alessia Formica, Alberto Nicolucci, Simone Palma, Maria Antonietta Pascali, Stefania Pieroni, Charlotte Trombadori, Sara Colantonio, Michela Franchini, Sabrina Molinaro
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GA-UNet: A Lightweight Ghost and Attention U-Net for Medical Image Segmentation J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-13 Bo Pang, Lianghong Chen, Qingchuan Tao, Enhui Wang, Yanmei Yu
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CT-Based Evaluation of the Shape of the Diaphragm Using 3D Slicer J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-11
Abstract The diaphragm is the main inspiratory muscle and separates the thorax and the abdomen. In COPD, the evaluation of the diaphragm shape is clinically important, especially in the case of hyperinflation. However, delineating the diaphragm remains a challenge as it cannot be seen entirely on CT scans. Therefore, the lungs, ribs, sternum, and lumbar vertebrae are used as surrogate landmarks to
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Classification of Lung Diseases Using an Attention-Based Modified DenseNet Model J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-11 Upasana Chutia, Anand Shanker Tewari, Jyoti Prakash Singh, Vikash Kumar Raj
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Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-08 Kuniki Imagawa, Kohei Shiomoto
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Feature Fusion for Multi-Coil Compressed MR Image Reconstruction J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-08 Hang Cheng, Xuewen Hou, Gang Huang, Shouqiang Jia, Guang Yang, Shengdong Nie
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Effects of Intravenous Infusion of Iodine Contrast Media on the Tracheal Diameter and Lung Volume Measured with Deep Learning-Based Algorithm J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-06 Koichiro Yasaka, Hiroyuki Saigusa, Osamu Abe
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Development and Validation of Multimodal Models to Predict the 30-Day Mortality of ICU Patients Based on Clinical Parameters and Chest X-Rays J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-06 Jiaxi Lin, Jin Yang, Minyue Yin, Yuxiu Tang, Liquan Chen, Chang Xu, Shiqi Zhu, Jingwen Gao, Lu Liu, Xiaolin Liu, Chenqi Gu, Zhou Huang, Yao Wei, Jinzhou Zhu
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Identification and Localization of Indolent and Aggressive Prostate Cancers Using Multilevel Bi-LSTM J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-06 Afnan M. Alhassan
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Computerized Segmentation Method for Nonmasses on Breast DCE-MRI Images Using ResUNet++ with Slice Sequence Learning and Cross-Phase Convolution J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-05 Akiyoshi Hizukuri, Ryohei Nakayama, Mariko Goto, Koji Sakai
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Prediction of Ablation Rate for High-Intensity Focused Ultrasound Therapy of Adenomyosis in MR Images Based on Multi-model Fusion J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-05
Abstract This study aimed to develop a model based on radiomics and deep learning features to predict the ablation rate in patients with adenomyosis undergoing high-intensity focused ultrasound (HIFU) therapy. A total of 119 patients with adenomyosis who received HIFU therapy were retrospectively analyzed. Participants were included in the training and testing queues in a 7:3 ratio. Radiomics features
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DilatedToothSegNet: Tooth Segmentation Network on 3D Dental Meshes Through Increasing Receptive Vision J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-05 Lucas Krenmayr, Reinhold von Schwerin, Daniel Schaudt, Pascal Riedel, Alexander Hafner
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Independently Trained Multi-Scale Registration Network Based on Image Pyramid J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-05 Qing Chang, Yaqi Wang, Jieming Zhang
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From CNN to Transformer: A Review of Medical Image Segmentation Models J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-04
Abstract Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely adopted approach currently is U-Net and its variants. Moreover, with the remarkable success of pre-trained models in natural language processing
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Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-04
Abstract Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, image compression, among others. In light of this, the widespread popularity of deep learning (DL) and machine
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Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-04 Mohammad Amin Salehi, Hamid Harandi, Soheil Mohammadi, Mohammad Shahrabi Farahani, Shayan Shojaei, Ramy R. Saleh
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Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-04 H. J. H. Dreesen, C. Stroszczynski, M. M. Lell
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From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-01 Arshi Parvaiz, Esha Sadia Nasir, Muhammad Moazam Fraz
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Correlation Between Cognitive Impairment and Lenticulostriate Arteries: A Clinical and Radiomics Analysis J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-01 Langtao Zhou, Huiting Wu, Hong Zhou
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Auto-BCS: A Hybrid System for Real-Time Breast Cancer Screening from Pathological Images J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-01 Ekta, Vandana Bhatia
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Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs—A Preliminary Study J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-01 Chenyu Jiang, Jingxin Zhang, Wenhuan Li, Yali Li, Ming Ni, Dan Jin, Yan Zhang, Liang Jiang, Huishu Yuan
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A Systematic Review on Caries Detection, Classification, and Segmentation from X-Ray Images: Methods, Datasets, Evaluation, and Open Opportunities J. Digit. Imaging (IF 4.4) Pub Date : 2024-03-01 Luiz Guilherme Kasputis Zanini, Izabel Regina Fischer Rubira-Bullen, Fátima de Lourdes dos Santos Nunes
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A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-29 Jianning Chi, Zhiyi Sun, Shuyu Tian, Huan Wang, Siqi Wang
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Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn’s Disease and Intestinal Tuberculosis J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-29
Abstract This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB). A total of 330 patients with pathologically confirmed as CD or ITB from the First Affiliated Hospital of Zhengzhou University were divided into the validation dataset one (CD: 167; ITB: 57) and validation dataset two (CD: 78;
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Privacy-Preserving Breast Cancer Classification: A Federated Transfer Learning Approach J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-29 Selvakanmani S, G Dharani Devi, Rekha V, J Jeyalakshmi
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A Multiparametric MRI-based Radiomics Model for Stratifying Postoperative Recurrence in Luminal B Breast Cancer J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-29 Kepei Xu, Meiqi Hua, Ting Mai, Xiaojing Ren, Xiaozheng Fang, Chunjie Wang, Min Ge, Hua Qian, Maosheng Xu, Ruixin Zhang
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SC-Unext: A Lightweight Image Segmentation Model with Cellular Mechanism for Breast Ultrasound Tumor Diagnosis J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-29 Fenglin Cai, Jiaying Wen, Fangzhou He, Yulong Xia, Weijun Xu, Yong Zhang, Li Jiang, Jie Li
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URI-CADS: A Fully Automated Computer-Aided Diagnosis System for Ultrasound Renal Imaging J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-27 Miguel Molina-Moreno, Iván González-Díaz, Maite Rivera Gorrín, Víctor Burguera Vion, Fernando Díaz-de-María
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Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-27 M. Pytlarz, K. Wojnicki, P. Pilanc, B. Kaminska, A. Crimi
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LAMA: Lesion-Aware Mixup Augmentation for Skin Lesion Segmentation J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-26 Norsang Lama, Ronald Joe Stanley, Binita Lama, Akanksha Maurya, Anand Nambisan, Jason Hagerty, Thanh Phan, William Van Stoecker
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OralEpitheliumDB: A Dataset for Oral Epithelial Dysplasia Image Segmentation and Classification J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-26 Adriano Barbosa Silva, Alessandro Santana Martins, Thaína Aparecida Azevedo Tosta, Adriano Mota Loyola, Sérgio Vitorino Cardoso, Leandro Alves Neves, Paulo Rogério de Faria, Marcelo Zanchetta do Nascimento
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HBMD-Net: Feature Fusion Based Breast Cancer Classification with Class Imbalance Resolution J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-26
Abstract Breast cancer, a widespread global disease, represents a significant threat to women’s health and lives, ranking as one of the most vulnerable malignant tumors they face. Many researchers have proposed their computer-aided diagnosis systems for classifying breast cancer. The majority of these approaches primarily utilize deep learning (DL) methods, which are not entirely reliable. These approaches
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An Automatic Grading System for Orthodontically Induced External Root Resorption Based on Deep Convolutional Neural Network J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-23 Shuxi Xu, Houli Peng, Lanxin Yang, Wenjie Zhong, Xiang Gao, Jinlin Song
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Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-23
Abstract The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with preoperative MRI and clinical factors in predicting the treatment response of unresectable hepatocellular carcinoma (HCC) patients receiving hepatic arterial infusion chemotherapy (HAIC). A total of 191 patients with unresectable HCC who underwent HAIC in our hospital between May 2019 and March
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Comparing Strain Assessment in Compressed Sensing and Conventional Cine MRI J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-22 Kaixuan Yao, Wei Deng, Rong He, Hui Gao, Linlin Wang, Ren Zhao, Xiuzheng Yue, Yongqiang Yu, Liang Zhong, Xiaohu Li
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Towards an EKG for SBO: A Neural Network for Detection and Characterization of Bowel Obstruction on CT J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-22 Paul M. Murphy
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An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-22 Weidong Wang, Hongme Zhang, Yizhen Li, Yi Wang, Qingfeng Zhang, Geqi Ding, Lixue Yin, Jinshan Tang, Bo Peng
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BTK Expression Level Prediction and the High-Grade Glioma Prognosis Using Radiomic Machine Learning Models J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21 Chenggang Jiang, Chen Sun, Xi Wang, Shunchang Ma, Wang Jia, Dainan Zhang
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Constructing the Optimal Classification Model for Benign and Malignant Breast Tumors Based on Multifeature Analysis from Multimodal Images J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21
Abstract The purpose of this study was to fuse conventional radiomic and deep features from digital breast tomosynthesis craniocaudal projection (DBT-CC) and ultrasound (US) images to establish a multimodal benign-malignant classification model and evaluate its clinical value. Data were obtained from a total of 487 patients at three centers, each of whom underwent DBT-CC and US examinations. A total
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Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21 Wuqi Li, Shitong Mao, Amanda S. Mahoney, James L. Coyle, Ervin Sejdić
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A Comparative Study of Performance Between Federated Learning and Centralized Learning Using Pathological Image of Endometrial Cancer J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21 Jong Chan Yeom, Jae Hoon Kim, Young Jae Kim, Jisup Kim, Kwang Gi Kim
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Approximating Intermediate Feature Maps of Self-Supervised Convolution Neural Network to Learn Hard Positive Representations in Chest Radiography J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21 Kyungjin Cho, Ki Duk Kim, Jiheon Jeong, Yujin Nam, Jeeyoung Kim, Changyong Choi, Soyoung Lee, Gil-Sun Hong, Joon Beom Seo, Namkug Kim
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DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21 Dina A. Ragab, Salema Fayed, Noha Ghatwary
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Auto-segmentation of Adult-Type Diffuse Gliomas: Comparison of Transfer Learning-Based Convolutional Neural Network Model vs. Radiologists J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21
Abstract Segmentation of glioma is crucial for quantitative brain tumor assessment, to guide therapeutic research and clinical management, but very time-consuming. Fully automated tools for the segmentation of multi-sequence MRI are needed. We developed and pretrained a deep learning (DL) model using publicly available datasets A (n = 210) and B (n = 369) containing FLAIR, T2WI, and contrast-enhanced
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Developing a Radiomics Atlas Dataset of normal Abdominal and Pelvic computed Tomography (RADAPT) J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-21
Abstract Atlases of normal genomics, transcriptomics, proteomics, and metabolomics have been published in an attempt to understand the biological phenotype in health and disease and to set the basis of comprehensive comparative omics studies. No such atlas exists for radiomics data. The purpose of this study was to systematically create a radiomics dataset of normal abdominal and pelvic radiomics that
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Low-Dose CT Image Super-resolution Network with Noise Inhibition Based on Feedback Feature Distillation Mechanism J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-20 Jianning Chi, Xiaolin Wei, Zhiyi Sun, Yongming Yang, Bin Yang
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Radiomics Features on Enhanced Computed Tomography Predict FOXP3 Expression and Clinical Prognosis in Patients with Head and Neck Squamous Cell Carcinoma J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-20 Yi Wang, Juan Ye, Kai Zhou, Nian Chen, Gang Huang, Guangyong Feng, Guihai Zhang, Xiaoxia Gou
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Image Omics Nomogram Based on Incoherent Motion Diffusion-Weighted Imaging in Voxels Predicts ATRX Gene Mutation Status of Brain Glioma Patients J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-20 Xueyao Lin, Chaochao Wang, Jingjing Zheng, Mengru Liu, Ming Li, Hongbin Xu, Haibo Dong
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Automated Segmentation and Diagnostic Measurement for the Evaluation of Cervical Spine Injuries Using X-Rays J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-20 Jae Hyuk Shim, Woo Seok Kim, Kwang Gi Kim, Gi Taek Yee, Young Jae Kim, Tae Seok Jeong
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Predicting Mismatch Repair Deficiency Status in Endometrial Cancer through Multi-Resolution Ensemble Learning in Digital Pathology J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-20 Jongwook Whangbo, Young Seop Lee, Young Jae Kim, Jisup Kim, Kwang Gi Kim
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Patient Re-Identification Based on Deep Metric Learning in Trunk Computed Tomography Images Acquired from Devices from Different Vendors J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-16 Yasuyuki Ueda, Daiki Ogawa, Takayuki Ishida
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Visualizing Clinical Data Retrieval and Curation in Multimodal Healthcare AI Research: A Technical Note on RIL-workflow J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-16 Ali Ganjizadeh, Stephanie J. Zawada, Steve G. Langer, Bradley J. Erickson
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A Motion-Aware DNN Model with Edge Focus Loss and Quality Control for Short-Axis Left Ventricle Segmentation of Cine MR Sequences J. Digit. Imaging (IF 4.4) Pub Date : 2024-02-16 Yu Wang, Zheng Sun, Zhi Liu, Jie Lu, Nan Zhang