Understanding perception of the radiology community concerning virtual reality (VR) and augmented reality (AR) technology in radiology education by Suneet Paulson, Dwight Figueiredo, Sushant Matre

“…Abstract Background Radiology education is crucial in developing the fundamental skills and knowledge for effectively interpreting medical images, planning interventions, and providing high-quality patient care. …”
Get full text

Advancing breast cancer diagnosis: token vision transformers for faster and accurate classification of histopathology images by Mouhamed Laid Abimouloud, Khaled Bensid, Mohamed Elleuch, Mohamed Ben Ammar, Monji Kherallah

“…Abstract The vision transformer (ViT) architecture, with its attention mechanism based on multi-head attention layers, has been widely adopted in various computer-aided diagnosis tasks due to its effectiveness in processing medical image information. ViTs are notably recognized for their complex architecture, which requires high-performance GPUs or CPUs for efficient model training and deployment in real-world medical diagnostic devices. …”
Get full text

Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images by Miao Wu, Chuanbo Yan, Gan Sen

“…The observations of the study imply that transfer learning is a useful technique when the availability of medical images is limited. The proposed classification system by using deep CNN features and SVM classifier is potentially helpful for clinicians to improve their HCE diagnostic performance in clinical practice.…”
Get full text

Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Conclusions: To the best of our knowledge, the DNetPRO algorithm was applied for the first time to medical image analysis and proved suitable for the selection of radiomic features with the highest predictive power, a crucial step in a radiomic pipeline. …”
Get full text

Repeatability, reproducibility, and the effects of radiotherapy on radiomic features of lowfield MR-LINAC images of the prostate by Parker Anderson, Nesrin Dogan, John Chetley Ford, Kyle Padgett, Garrett Simpson, Radka Stoyanova, Matthew Charles Abramowitz, Alan Dal Pra, Rodrigo Delgadillo

“…Through radiomics, a quantitative analysis of medical images, it is possible to adapt treatment early on, which may prevent or mitigate future adverse events. …”
Get full text

FBATCNet: A Temporal Convolutional Network With Frequency Band Attention for Decoding Motor Imagery EEG by Shuaishuai Ma, Jidong Lv, Wenjie Li, Yan Liu, Ling Zou, Yakang Dai

Get full text

Deep learning-based algorithm for classifying high-resolution computed tomography features in coal workers’ pneumoconiosis by Hantian Dong, Biaokai Zhu, Xiaomei Kong, Xuesen Su, Ting Liu, Xinri Zhang

“…Methods All chest high-resolution computed tomography (HRCT) medical images presented in this work were obtained from 217 coal workers' pneumoconiosis (CWP) patients and dust-exposed workers. …”
Get full text

Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy by Qi Wan, Clifford Lindsay, Chenxi Zhang, Jisoo Kim, Xin Chen, Jing Li, Raymond Y. Huang, David A. Reardon, Geoffrey S. Young, Lei Qin

“…Abstract Background Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. …”
Get full text

Advanced colon cancer detection: Integrating context-aware multi-image fusion (Camif) in a multi-stage framework by M.V.R. Vittal

“…., demonstrating its effectiveness and potential for clinical applications in medical image analysis. The results indicate the proposed method’s high efficacy, achieving an F1 score of 99.31. …”
Get full text

The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets by Theresa Willem, Alessandro Wollek, Theodor Cheslerean-Boghiu, Martha Kenney, Alena Buyx

“…As a standard, categorical data, such as patients’ gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population. …”
Get full text

The relationship between autonomy, optimism, work engagement and organisational citizenship behaviour among nurses fighting COVID-19 in Wuhan: a serial multiple mediation by Yang Liu, Hui Zhang, Yi Zhao, Leiwen Tang, Jing Shao, Zhihong Ye, Dandan Chen, Ping Zou, Shuanghong Lin

Get full text

Application of Fractal Analysis in Detecting Trabecular Bone Changes in Periapical Radiograph of Patients with Periodontitis by Parisa Soltani, Sajad Sami, Jaber Yaghini, Ehsan Golkar, Francesco Riccitiello, Gianrico Spagnuolo

Get full text

Systematic Coronary Risk Evaluation 2 (SCORE2), arterial stiffness, and subclinical coronary atherosclerosis in a population-based study by Susanna Strömberg, Andreas Stomby, Jan Engvall, Carl Johan Östgren

Get full text

Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…Transformers are a promising deep learning approach for automated medical image segmentation. ObjectiveThis scoping review will synthesize current literature and assess the use of various transformer models for neuroimaging segmentation. …”
Get full text

Which muscle is the external rotation compensator after superior capsular reconstruction? by Nattakorn Mahasupachai, MD, Nobuyuki Yamamoto, MD, PhD, Atsushi Arino, MD, Jun Kawakami, MD, PhD, Rei Kimura, MD, Toshimi Aizawa, MD, PhD

“…Posterior deltoid and teres minor volume were measured using open-source medical image processing software preoperatively and 1-year postoperatively. …”
Get full text

Brain Age Prediction Using a Lightweight Convolutional Neural Network by Fatma Eltashani, Mario Parreno-Centeno, James H. Cole, Joao Paulo Papa, Fumie Costen

Get full text

Compensatory increase in oxygen extraction fraction is associated with age-related cerebrovascular disease by John McFadden, Julian Matthews, Lauren Scott, Karl Herholz, Ben Dickie, Hamied Haroon, Oliver Sparasci, Saadat Ahmed, Natalia Kyrtata, Geoffrey J.M. Parker, Hedley C.A. Emsley, Joel Handley, Maélène Lohezic, Laura M. Parkes

Get full text

Percutaneous unilateral biportal endoscopic discectomy for symptomatic lumbar disc herniation in geriatric patients by Rongqing Qin, Rongqing Qin, Anhong Guan, Anhong Guan, Min Zhu, Pin Zhou, Bing Zhou, Bing Zhou, Ruihua Zhou, Ruihua Zhou, Zaiyong Guan, Zaiyong Guan

Get full text

Prevalence of Myocardial Infarction With Obstructive and Non-Obstructive Coronary Arteries in a Middle-Aged Population With Chronic Airflow Limitation: A Cross-Sectional Study by Sundh J, Ekström M, Blomberg A, Lindberg E, Malinovschi A, Olin AC, Sköld CM, Torén K, Wollmer P, Östgren CJ, Jernberg T

“…Josefin Sundh,1 Magnus Ekström,2 Anders Blomberg,3 Eva Lindberg,4 Andrei Malinovschi,5 Anna-Carin Olin,6 C Magnus Sköld,7,8 Kjell Torén,6 Per Wollmer,6 Carl Johan Östgren,9,10 Tomas Jernberg11,12 1Department of Respiratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden; 2Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Respiratory Medicine, Allergology and Palliative Medicine, Lund, Sweden; 3Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; 4Department of Medical Sciences, Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden; 5Department of Medical Sciences, Clinical Physiology, Uppsala University, Uppsala, Sweden; 6Occupational and Environmental Medicine, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; 7Respiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; 8Department of Respiratory Medicine and Allergy, Karolinska University Hospital, Stockholm, Sweden; 9Department of Translational Medicine, Lund University, Malmö, Sweden; 10Centre of Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; 11Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; 12Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, SwedenCorrespondence: Josefin Sundh, Department of Respiratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, 701 82, Sweden, Tel +46702349517, Email josefin.sundh@regionorebrolan.se; josefin.sundh@oru.sePurpose: Myocardial infarctions (MIs) can occur in underlying obstructive coronary artery disease (MI-CAD) or in non-obstructive coronary arteries (MINOCA). …”
Get full text

Unveiling GPT-4V's hidden challenges behind high accuracy on USMLE questions: Observational Study by Zhichao Yang, Zonghai Yao, Mahbuba Tasmin, Parth Vashisht, Won Seok Jang, Feiyun Ouyang, Beining Wang, David McManus, Dan Berlowitz, Hong Yu

“…However, the ability of these models to interpret medical images remains underexplored. ObjectiveThis study aimed to comprehensively evaluate the performance, interpretability, and limitations of GPT-3.5 Turbo, GPT-4, and its successor, GPT-4 Vision (GPT-4V), specifically focusing on GPT-4V’s newly introduced image-understanding feature. …”
Get full text