Table of Contents

• Learning to triage by learning to reconstruct: a generative self-supervised approach for prostate cancer based on axial T2w MRIAlvaro Fernandez-Quilez, Trygve Eftestøl, Svein Reidar Kjosavik, Ketil Oppedal. [doi]
• Retinal layer segmentation for age-related macular degeneration patients with 3D-UNetSouvick Mukherjee, Tharindu De Silva, Gopal Jayakar, Peyton Grisso, Henry E. Wiley, Tiarnan D. Keenan, Alisa T. Thavikulwat, Emily Y. Chew, Catherine Cukras. [doi]
• DBNet: a dual-branch network for breast cancer classification in ultrasound imagesHui Meng, Qingfeng Li, Xuefeng Liu, Yong Wang, Jianwei Niu 0002. [doi]
• Improving lesion detection algorithm in digital breast tomosynthesis leveraging ensemble cross-validation models with multi-depth levelsBelayat Hossain, Robert M. Nishikawa, Juhun Lee. [doi]
• Automatic polyp detection using SmartEndo-Net based on fusion feature pyramid network with mix-up edgesYoung-Jae Kim, Sohyun Byun, Chung il Ahn, Sangwook Cho, Kwang Gi Kim. [doi]
• Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CTFakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin, Ehsan Samei, Joseph Y. Lo. [doi]
• BAPGAN: GAN-based bone age progression of femur and phalange x-ray imagesShinji Nakazawa, Changhee Han, Joe Hasei, Ryuichi Nakahara, Toshifumi Ozaki. [doi]
• Taking full advantage of uncertainty estimation: an uncertainty-assisted two-stage pipeline for multi-organ segmentationZhou Zheng, Masahiro Oda, Kazunari Misawa, Kensaku Mori. [doi]
• Machine learning algorithm for classification of breast ultrasound imagesJennie Karlsson, Jennifer Ramkull, Ida Arvidsson, Anders Heyden, Kalle Åström, Niels Christian Overgaard, Kristina Lång. [doi]
• Contrastive learning meets transfer learning: a case study in medical image analysisYuzhe Lu, Aadarsh Jha, Ruining Deng, Yuankai Huo. [doi]
• Unsupervised optical small bowel ischemia detection in a preclinical model using convolutional variational autoencodersGyeong Woo Cheon, So Hyun Nam, Jaepyeong Cha. [doi]
• Lymph node detection in T2 MRI with transformersTejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton, Thomas C. Shen, Yifan Peng, Zhiyong Lu, Ronald M. Summers. [doi]
• Early prediction of the Alzheimer's disease risk using Tau-PET and machine learningLujia Wang, Zhiyang Zheng, Yi Su, Kewei Chen 0001, David Weidman, Teresa Wu, Ben Lo, Fleming Lure, Jing Li 0016. [doi]
• CT radiomics to predict early hepatic recurrence after resection for intrahepatic cholangiocarcinomaJayasree Chakraborty, Joshua S. Jolissaint, Tiegong Wang, Kevin C. Soares, Mithat Gonen, Linda M. Pak, Thomas Börner, Richard K. G. Do, Vinod P. Balachandran, Michael I. D'Angelica, Jeffrey A. Drebin, T. Peter Kingham, Alice C. Wei, William R. Jarnagin. [doi]
• Deciphering deep ensembles for lung nodule analysisRavi K. Samala, Berkman Sahiner, Gene Pennello, Kenny H. Cha, Mohammad Mehdi Farhangi, Nicholas Petrick. [doi]
• Universal lesion detection in CT scans using neural network ensemblesTarun Mattikalli, Tejas Sudharshan Mathai, Ronald M. Summers. [doi]
• DG-GRU: dynamic graph based gated recurrent unit for age and gender prediction using brain imagingAnees Kazi, Viktoria Markova, Prabhat R. Kondamadugula, Beiyan Liu, Ahmed Adly, Shahrooz Faghihroohi, Nassir Navab. [doi]
• Colorectal polyp classification using confidence-calibrated convolutional neural networksKoen C. Kusters, Thom Scheeve, Nikoo Dehghani, Quirine E. W. van der Zander, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With. [doi]
• Computer-aided detection for architectural distortion: a comparison of digital breast tomosynthesis and digital mammographyYue Li, Zilong He, Xiangyuan Ma, Weixiong Zeng, Jialing Liu, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefang Wu, Weiguo Chen, Yao Lu 0007. [doi]
• Stroke lesion localization in 3D MRI datasets with deep reinforcement learningSamuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert. [doi]
• Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age predictionMarcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer. [doi]
• Cardiovascular disease and all-cause mortality risk prediction from abdominal CT using deep learningDaniel C. Elton, Andy Chen, Perry J. Pickhardt, Ronald M. Summers. [doi]
• Identifying sinus invasion in meningioma patients before surgery with deep learningQi Qiu, Kai Sun, Jing Zhang, Panpan Liu, Liang Wang, Junting Zhang, Junlin Zhou, Zhenyu Liu, Jie Tian 0001. [doi]
• Avalanche decision schemes to improve pediatric rib fracture detectionJonathan Burkow, Gregory Holste, Jeffrey Otjen, Francisco Perez, Joseph Junewick, Adam M. Alessio. [doi]
• Deep curriculum learning in task space for multi-class based mammography diagnosisJun Luo 0010, Dooman Arefan, Margarita Zuley, Jules H. Sumkin, Shandong Wu. [doi]
• Deep learning based multiple sclerosis lesion detection utilizing synthetic data generation and soft attention mechanismOmer Zucker Shmueli, Chen Solomon, Noam Ben-Eliezer, Hayit Greenspan. [doi]
• Similarity-based uncertainty scores for computer-aided diagnosisClaire Weissman, Lilly Roelofs, Jacob Furst 0001, Daniela Stan Raicu, Roselyne Tchoua. [doi]
• A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumorsIpsa Yadav, Marwa Ismail, Volodymyr Statsevych, Virginia B. Hill, Ramon Correa, Manmeet Ahluwalia, Pallavi Tiwari. [doi]
• AI-human interactive pipeline with feedback to accelerate medical image annotationYoungwon Choi, Marlena Garcia, Steven S. Raman, Dieter R. Enzmann, Matthew S. Brown. [doi]
• Applying a novel two-stage deep-learning model to improve accuracy in detecting retinal fundus imagesSai Kiran Reddy Maryada, William Booker, Gopichandh Danala, Catherine An Ha, Sanjana Mudduluru, Dean F. Hougen, Bin Zheng 0001. [doi]
• Real-time esophagus achalasia detection method for esophagoscopy assistanceKai Jiang, Masahiro Oda, Hironari Shiwaku, Masashi Misawa, Kensaku Mori. [doi]
• Addressing imaging accessibility by cross-modality transfer learningZhiyang Zheng, Yi Su, Kewei Chen 0001, David Weidman, Teresa Wu, Ben Lo, Fleming Lure, Jing Li 0016. [doi]
• Semi-supervised learning approach for automatic detection of hyperreflective foci in SD-OCT imagingTharindu De Silva, Kristina Heß, Cameron Duic, Souvick Mukherjee, Hector Sandoval, Jessica Aduwo, Tiarnan D. Keenan, Emily Y. Chew, Catherine Cukras. [doi]
• Linked psychopathology-specific factors and individual structural brain abnormalities in schizophreniaLin Chai, Yaping Wang, Weiyang Shi, Yu Zhang, Bing Liu, Tianzi Jiang, Lingzhong Fan. [doi]
• Prediction of TNM stage in head and neck cancer using hybrid machine learning systems and radiomics featuresMohammad R. Salmanpour, Mahdi Hosseinzadeh, Azizeh Akbari, Kasra Borazjani, Kasra Mojallal, Dariush Askari, Ghasem Hajianfar, Seyed Masoud Rezaeijo, Mohammad M. Ghaemi, Amir Hossein Nabizadeh, Arman Rahmim. [doi]
• Multi-stage investigation of deep neural networks for COVID-19 B-line feature detection in simulated and in vivo ultrasound imagesBenjamin Frey, Lingyi Zhao, Tiffany Clair Fong, Muyinatu A. Lediju Bell. [doi]
• Evaluating the sensitivity of deep learning to inter-reader variations in lesion delineations on bi-parametric MRI in identifying clinically significant prostate cancerAnsh Roge, Amogh Hiremath, Michael Sobota, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, Justin Ream, Ryan Ward, Halimat Olaniyan, Sadhna Verma, Andrei Purysko, Anant Madabhushi, Rakesh Shiradkar. [doi]
• A graph-theoretic algorithm for small bowel path tracking in CT scansSeung Yeon Shin, Sungwon Lee, Ronald M. Summers. [doi]
• Clinical outcome prediction in COVID-19 using self-supervised vision transformer representationsAishik Konwer, Prateek Prasanna. [doi]
• Predicting hematoma expansion after spontaneous intracranial hemorrhage through a radiomics based modelSamantha E. Seymour, Ryan A. Rava, Dennis Swetz, Andre Montiero, Ammad Baig, Kurt Schultz, Kenneth V. Snyder, Mohammad Waqas, Jason M. Davies, Elad I. Levy, Adnan H. Siddiqui, Ciprian N. Ionita. [doi]
• 4D radiomics in dynamic contrast-enhanced MRI: prediction of pathological complete response and systemic recurrence in triple-negative breast cancerMarco Caballo, Wendelien B. G. Sanderink, Luyi Han, Yuan Gao, Alexandra Athanasiou, Ritse M. Mann. [doi]
• One class to rule them all: detection and classification of prostate tumors presence in bi-parametric MRI based on auto-encodersAlvaro Fernandez-Quilez, Habib Ullah, Trygve Eftestøl, Svein Reidar Kjosavik, Ketil Oppedal. [doi]
• Deep learning-based longitudinal CT registration for anatomy variation assessment during radiotherapyYabo Fu, Yang Lei 0002, Zhen Tian, Tonghe Wang, Xianjin Dai, Jun Zhou, Mark McDonald, Jeffrey D. Bradley, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Placenta accreta spectrum and hysterectomy prediction using MRI radiomic featuresKa'Toria N. Leitch, Maysam Shahedi, James D. Dormer, Quyen N. Do, Yin Xi, Matthew A. Lewis, Christina L. Herrera, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler, Baowei Fei. [doi]
• Detecting aggressive papillary thyroid carcinoma using hyperspectral imaging and radiomic featuresKa'Toria N. Leitch, Martin T. Halicek, Maysam Shahedi, James V. Little, Amy Y. Chen, Baowei Fei. [doi]
• Annotation and segmentation of diabetic retinopathy lesions: an explainable AI applicationHoda Kheradfallah, Janarthanam Jothi Balaji, Varadharajan Jayakumar, Mohammed Abdul Rasheed, Vasudevan Lakshminarayanan. [doi]
• Effect of different molecular subtype reference standards in AI training: implications for DCE-MRI radiomics of breast cancersHeather M. Whitney, Yu Ji, Hui Li 0024, Peifang Liu, Maryellen L. Giger. [doi]
• Automated segmentation of pediatric brain tumors based on multi-parametric MRI and deep learningRachel Madhogarhia, Anahita Fathi Kazerooni, Sherjeel Arif, Jeffrey B. Ware, Ariana M. Familiar, Lorenna Vidal, Sina Bagheri, Hannah Anderson, Debanjan Haldar, Sophie Yagoda, Erin Graves, Michael Spadola, Rachel Yan, Nadia Dahmane, Chiharu Sako, Arastoo Vossough, Phillip B. Storm, Adam C. Resnick, Christos Davatzikos, Ali Nabavizadeh. [doi]
• Neurovascular bundles segmentation on MRI via hierarchical object activation networkYang Lei 0002, Tonghe Wang, Justin Roper, Sibo Tian, Pretesh Patel, Jeffrey D. Bradley, Ashesh B. Jani, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Exploring directed network connectivity in complex systems using large-scale augmented Granger causality (lsAGC)Axel Wismüller, M. Ali Vosoughi, Adora M. DSouza, Anas Z. Abidin. [doi]
• CNN-based tumor progression prediction after thermal ablation with CT imagingMarjaneh Taghavi, Monique Maas, Femke C. R. Staal, Regina G. H. Beets-Tan, Sean Benson. [doi]
• Incorporate radiograph-reading behavior and knowledge into deep reinforcement learning for lesion localizationDegan Hao, Dooman Arefan, Shandong Wu. [doi]
• A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorderEmma A. M. Stanley, Deepthi Rajashekar, Pauline Mouches, Matthias Wilms, Kira Plettl, Nils D. Forkert. [doi]
• Deep ensemble models with multiscale lung-focused patches for pneumonia classification on chest x-rayYoon Jo Kim, Jinseo An, Helen Hong. [doi]
• Open-world active learning for echocardiography view classificationGhada Zamzmi, Tochi Oguguo, Sivaramakrishnan Rajaraman, Sameer K. Antani. [doi]
• Early detection of oesophageal cancer through colour contrast enhancement for data augmentationXiaohong W. Gao, Stephen Taylor, Wei Pang 0001, Xin Lu, Barbara Braden. [doi]
• WRDet: a breast cancer detector for full-field digital mammogramsYen Nhi Truong Vu, Brent Mombourquette, Thomas Paul Matthews, Jason Su, Sadanand Singh. [doi]
• Fusion of clinical phenotypic and multi-modal MRI for acute bilirubin encephalopathy classificationXiangJun Chen, Zhaohui Wang, Yuefu Zhan, Faouzi Alaya Cheikh, Mohib Ullah. [doi]
• Interpretable learning approaches in structural MRI: 3D-ResNet fused attention for autism spectrum disorder classificationXiangJun Chen, Zhaohui Wang, Yuefu Zhan, Faouzi Alaya Cheikh, Mohib Ullah. [doi]
• Multi-class prediction for improving intestine segmentation on non-fecal-tagged CT volumeHirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori. [doi]
• Self-supervised U-Net for segmenting flat and sessile polypsDebayan Bhattacharya, Christian Betz, Dennis Eggert, Alexander Schlaefer. [doi]
• Segmentation of multiple myeloma plasma cells in microscopy images with noisy labelsÁlvaro García-Faura, Dejan Stepec, Tomaz Martincic, Danijel Skocaj. [doi]
• Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumesMasahiro Oda, Tong Zheng 0001, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto M. D., Toshiaki Akashi, Shigeki Aoki, Kensaku Mori. [doi]
• Deep learning with vessel surface meshes for intracranial aneurysm detectionKimberley M. Timmins, Irene C. van der Schaaf, Iris N. Vos, Ynte M. Ruigrok, Birgitta K. Velthuis, Hugo J. Kuijf. [doi]
• Normalization of MRI signal intensity in polycystic kidney disease and the effect on radiomic featuresLinnea Kremer, Natalie Perri, Eliza Sorber, Arlene Chapman, Samuel G. Armato III. [doi]
• Renal tumor analysis using multi-phase abdominal CT imagesKento Nishihira, Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Yuuki Kobari, Atsushi Ikeda, Noboru Niki. [doi]
• Multi-modality classification between myxofibrosarcoma and myxoma using radiomics and machine learning modelsCan Cui 0006, Samuel R. Johnson, Cullen P. Moran, Katherine S. Hajdu, Joanna Shechtel, John J. Block, Brian Bingham, David Smith, Leo Y. Luo, Hakmook Kang, Jennifer L. Halpern, Herbert S. Schwartz, Ginger E. Holt, Joshua M. Lawrenz, Benoit M. Dawant. [doi]
• A novel CNN+LSTM approach to classify frontal chest x-rays for spine fracturesLarissa C. Schudlo, Yiting Xie, Kirstin Small, Benedikt Graf. [doi]
• Performance evaluation of lightweight convolutional neural networks on retinal lesion segmentationMarlin Siebert, Philipp Rostalski. [doi]
• Segmentation of aorta and main pulmonary artery of non-contrast CT images using U-Net for chronic thromboembolic pulmonary hypertension: evaluation of robustness to contacts with blood vesselsHidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Toshihiko Sugiura, Nobuhiro Tanabe, Masahiko Kusumoto, Masahiro Kaneko, Noboru Niki. [doi]
• A study on 3D classical versus GAN-based augmentation for MRI brain image to predict the diagnosis of dementia with Lewy bodies and Alzheimer's disease in a European multi-center studyPetter Minne, Alvaro Fernandez-Quilez, Dag Aarsland, Daniel Ferreira, Eric Westman, Afina W. Lemstra, Mara Ten Kate, Alessandro Padovani, Irene Rektorova, Laura Bonanni, Flavio Nobili, Milica G. Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Frédéric Blanc 0002, Angelo Antonini, Ketil Oppedal. [doi]
• Automated kidney segmentation by mask R-CNN in T2-weighted magnetic resonance imagingManu Goyal, Junyu Guo, Lauren Hinojosa, Keith Hulsey, Ivan Pedrosa. [doi]
• Automation of ischemic myocardial scar detection in cardiac magnetic resonance imaging of the left ventricle using machine learningMichael Udin, Ciprian N. Ionita, Saraswati Pokharel, Umesh Sharma. [doi]
• Fusion of multiple deep convolutional neural networks (DCNNs) for improved segmentation of lung nodules in CT imagesYifan Wang, Chuan Zhou 0002, Heang-Ping Chan, Lubomir M. Hadjiiski, Aamer Chughtai. [doi]
• Synthesis of annotated pathological retinal OCT data with pathology-induced deformationsHristina Uzunova, Leonie Basso, Jan Ehrhardt, Heinz Handels. [doi]
• Improving the performance of computer-aided classification of breast lesions using a new feature fusion methodWarid Islam, Gopichandh Danala, Huong Pham, Bin Zheng 0001. [doi]
• Improving prostate cancer triage with GAN-based synthetically generated prostate ADC MRIAlvaro Fernandez-Quilez, Omer Parvez, Trygve Eftestøl, Svein Reidar Kjosavik, Ketil Oppedal. [doi]
• Blood vessel segmentation in en-face OCTA images: a frequency based methodAnna Breger, Felix Goldbach, Bianca S. Gerendas, Ursula Schmidt-Erfurth, Martin Ehler. [doi]
• Effects of feature type and multiple scanners on brain metastasis stereotactic radiosurgery outcome predictionDavid DeVries, Frank Lagerwaard, Jaap Zindler, Timothy P. C. Yeung, George Rodrigues, George Hajdok, Aaron D. Ward. [doi]
• PET image harmonization using smoothing-CycleGANAbdullah Thabit, Shenpeng Li, Rob Williams, Victor L. Villemagne, Christopher C. Rowe, Vincent Doré, Pierrick Bourgeat. [doi]
• Mammary duct detection using self-supervised encodersShannon Doyle, Francesco Dal Canton, Jelle Wesseling, Clara I. Sánchez, Jonas Teuwen. [doi]
• Intrinsic subtype classification of breast lesions on mammograms by contrastive learningChisako Muramatsu, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita 0001. [doi]
• Image transformers for classifying acute lymphoblastic leukemiaPriscilla Cho, Sajal Dash, Aristeidis Tsaris, Hong-Jun Yoon. [doi]
• Prediction of CD3 T-cell infiltration status in colorectal liver metastases: a radiomics-based imaging biomarkerRalph Saber, David Henault, Eugene Vorontsov, Emmanuel Montagnon, An Tang, Simon Turcotte, Samuel Kadoury. [doi]
• Multi-institutional evaluation of a deep learning model for fully automated detection of aortic aneurysms in contrast and non-contrast CTYiting Xie, Benedikt Graf, Parisa Farzam, Brian Baker, Christine Lamoureux, Arkadiusz Sitek. [doi]
• Categorization of tumor-derived cells from lung cancer with compact deep learningYongjian Yu, Jue Wang. [doi]
• Transformation-consistent semi-supervised learning for prostate CT radiotherapyYichao Li, Mohamed S. Elmahdy, Michael S. Lew, Marius Staring. [doi]
• Uncertainty estimation in classification of MGMT using radiogenomics for glioblastoma patientsWalia Farzana, Zeina A. Shboul, Ahmed G. Temtam, Khan M. Iftekharuddin. [doi]
• Early prediction of metastasis in women with locally advanced breast cancerSimona Rabinovici-Cohen, Tal Tlusty, Xosé M. Fernández, Beatriz Grandal Rejo. [doi]
• Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patientsAlejandro Gutierrez, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert. [doi]
• Resampling and harmonization for mitigation of heterogeneity in imaging parameters: a comparative studyApurva Singh, Hannah Horng, Leonid Roshkovan, Michelle Hershman, Russell T. Shinohara, Sharyn Katz, Despina Kontos. [doi]
• Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexitySven Kuckertz, Jan Klein 0001, Christiane Engel, Benjamin Geisler, Stefan Kraß, Stefan Heldmann. [doi]
• Analyzing GAN artifacts for simulating mammograms: application towards finding mammographically-occult cancerJuhun Lee, Robert M. Nishikawa. [doi]
• A vector representation of local image contrast patterns for lesion classificationWeiguo Cao, Marc Jason Pomeroy, Yongfeng Gao, Perry J. Pickhardt, Almas F. Abbasi, Jela Bandovic, Zhengrong Liang. [doi]
• Can deep learning model undergo the same process as a human radiologist when determining malignancy of pulmonary nodules?Jun Keun Choi, Ehwa Yang, Chin A. Yi, Minsu Park, Jung Won Moon, Jae-Hun Kim. [doi]
• Hybrid transformer for lesion segmentation on adaptive optics retinal imagesJianfei Liu, Joanne Li, Amday Wolde, Catherine Cukras, Johnny Tam. [doi]
• A deep network ensemble for segmentation of cervical spinal cord and neural foraminaDavid Zarrin, Anshul Ratnaparkhi, Bayard Wilson, Kirstin Cook, Ien Li, Azim Laiwalla, Mark Attiah, Joel Beckett, Bilwaj Gaonkar, Luke Macyszyn. [doi]
• Fusion of handcrafted and deep transfer learning features to improve performance of breast lesion classificationMeredith A. Jones, Huong Pham, Tiancheng Gai, Bin Zheng 0001. [doi]
• Human-in-the-loop deep learning retinal image classification with customized loss functionSuhev Shakya, Mariana Vasquez, Yiyang Wang, Roselyne Tchoua, Jacob Furst 0001, Daniela Raicu. [doi]
• Prediction of lung CT scores of systemic sclerosis by cascaded regression neural networksJingnan Jia, Marius Staring, Irene Hernández-Girón, Lucia J. M. Kroft, Anne A. Schouffoer, Berend C. Stoel. [doi]
• CVT-Vnet: a convolutional-transformer model for head and neck multi-organ segmentationShaoyan Pan, Zhen Tian, Yang Lei 0002, Tonghe Wang, Jun Zhou, Mark McDonald, Jeffrey D. Bradley, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• High-resolution MR imaging using self-supervised parallel networkHuiqiao Xie, Yang Lei 0002, Tonghe Wang, Justin Roper, Jeffrey D. Bradley, Tian Liu 0004, Hui Mao, Xiaofeng Yang 0005. [doi]
• Identifying an optimal machine learning generated image marker to predict survival of gastric cancer patientsHuong Pham, Meredith A. Jones, Tiancheng Gai, Warid Islam, Gopichandh Danala, Javier A. Jo, Bin Zheng 0001. [doi]
• Radiomic texture feature descriptor to distinguish recurrent brain tumor from radiation necrosis using multimodal MRIMd. Shibly Sadique, Ahmed G. Temtam, E. Lappinen, Khan M. Iftekharuddin. [doi]
• Device specific SD-OCT retinal layer segmentation using cycle-generative adversarial networks in patients with AMDSouvick Mukherjee, Tharindu De Silva, Gopal Jayakar, Peyton Grisso, Henry E. Wiley, Tiarnan D. Keenan, Alisa T. Thavikulwat, Emily Y. Chew, Catherine Cukras. [doi]
• Deep pancreas segmentation through quantification of pancreatic uncertainty on abdominal CT imagesHyeon Dham Yoon, Hyeonjin Kim, Helen Hong. [doi]
• Multiparameter analysis of vascular remodeling in post-acute sequelae of COVID-19Catalin I. Fetita, Mathilde Maury, Aurélien Justet, Juliette Dindart, Jean Richeux, Lucile Sese, Nicolas Aide, Thomas Gille, Hilario Nunes, Jean-François Bernaudin, Pierre-Yves Brillet. [doi]
• Hepatic artery segmentation with 3D convolutional neural networksFarina Kock, Grzegorz Chlebus, Felix Thielke, Andrea Schenk, Hans Meine. [doi]
• Drug response prediction using deep neural network trained by adaptive resampling of histopathological imagesTomoharu Kiyuna, Noriko Motoi, Hiroshi Yoshida, Hidehito Horinouchi, Tatsuya Yoshida, Takashi Kohno, Shun-ichi Watanabe, Yuichiro Ohe, Atsushi Ochiai. [doi]
• Integrating zonal priors and pathomic MRI biomarkers for improved aggressive prostate cancer detection on MRIIndrani Bhattacharya, Wei Shao 0008, Simon J. C. Soerensen, Richard E. Fan, Jeffrey B. Wang, Christian Kunder, Pejman Ghanouni, Geoffrey A. Sonn, Mirabela Rusu. [doi]
• Effect of computerized decision support on diagnostic accuracy and intra-observer variability in multi-institutional observer performance study for bladder cancer treatment response assessment in CT urographyDi Sun, Lubomir M. Hadjiiski, Rohan Garje, Yousef Zakharia, Lauren Pomerantz, Monika Joshi, Ajjai Alva, Heang-Ping Chan, Richard H. Cohan, Elaine M. Caoili, Kenny H. Cha, Galina Kirova-Nedyalkova, Matthew S. Davenport, Prasad R. Shankar, Isaac R. Francis, Kimberly Shampain, Nathaniel Meyer, Daniel Barkmeier, Sean Woolen, Phillip L. Palmbos, Alon Z. Weizer, Ravi K. Samala, Chuan Zhou 0002, Martha M. Matuszak. [doi]
• A CT-based radiomics model for predicting feeding tube insertion in oropharyngeal cancerTricia Chinnery, Pencilla Lang, Anthony Nichols, Sarah A. Mattonen. [doi]
• Virtual vs. reality: external validation of COVID-19 classifiers using XCAT phantoms for chest computed tomographyFakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, William Paul Segars, Ehsan Samei, Joseph Y. Lo. [doi]
• Efficient endoscopic frame informativeness assessment by reusing the encoder of the primary CAD taskFidan Mammadli, Fons van der Sommen, Tim Boers, Joost van der Putten, Kiki N. Fockens, Jelmer B. Jukema, Martijn R. Jong, Jacques J. G. H. M. Bergman, Peter H. N. de With. [doi]
• Bayesian uncertainty estimation for detection of long-tail and unseen conditions in abdominal imagesMina Rezaei, Janne J. Näppi, Bernd Bischl, Hiroyuki Yoshida. [doi]
• Iterative ComBat methods for harmonization of radiomic featuresHannah Horng, Apurva Singh, Bardia Yousefi, Eric A. Cohen, Babak Haghighi, Sharyn Katz, Peter B. Noël, Russell T. Shinohara, Despina Kontos. [doi]
• A feasibility study of computer-aided diagnosis with DECT Bayesian reconstruction for polyp classificationShaojie Chang, Yongfeng Gao, Marc Jason Pomeroy, Siming Lu, Zhengrong Liang. [doi]
• Multi-channel medical image segmentation method in Hessian domainShuheng Cao, Ethan Yu, Aidan Clarke, Yongfeng Gao, Lihong Li 0002. [doi]
• A deep learning approach for COVID-19 screening and localization on chest x-ray imagesKarem Daiane Marcomini, Diego Armando Cardona Cárdenas, Agma Juci Machado Traina, José Eduardo Krieger, Marco Antonio Gutierrez 0001. [doi]
• Deep-learning characterization and quantification of COVID-19 pneumonia lesions from chest CT imagesDavid Bermejo-Peláez, Raúl San José Estépar, M. Fernández-Velilla, Carmelo Palacios Miras, Guillermo Gallardo Madueño, M. Benegas, Miguel A. Luengo-Oroz, J. Sellarés, M. Sánchez, Gorka Bastarrika, German R. Peces-Barba, Luis Miguel Seijo Maceiras, María J. Ledesma-Carbayo. [doi]
• Ensembling mitigates scanner effects in deep learning medical image segmentation with deep-U-NetsAnshul Ratnaparkhi, Bilwaj Gaonkar, David Zarrin, Ien Li, Kirstin Cook, Azim Laiwalla, Bayard Wilson, Mark Attiah, Christine S. Ahn, Diane Villaroman, Bryan Yoo, Banafsheh Salehi, Joel Beckett, Luke Macyszyn. [doi]
• Deep hybrid convolutional wavelet networks: application to predicting response to chemoradiation in rectal cancers via MRIAmir Reza Sadri, Thomas DeSilvio, Prathyush Chirra, Andrei Purysko, Rajmohan Paspulati, Kenneth Friedman, Smitha S. Krishnamurthi, David Liska, Sharon Stein, Satish E. Viswanath. [doi]
• Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid casesErikson Júlio De Aguiar, Karem D. Marcomini, Felipe A. Quirino, Marco A. Gutierrez 0001, Caetano Traina Jr., Agma J. M. Traina. [doi]
• Spotlight scheme: enhancing medical image classification with lesion location informationJing Ni, Qilei Chen, Ping Liu, Yu Cao 0002, Benyuan Liu. [doi]
• Optimization of imaging parameters of an investigational photon-counting CT prototype for lung lesion radiomicsCindy McCabe, Mojtaba Zarei, William Paul Segars, Ehsan Samei, Ehsan Abadi. [doi]
• A comparison of feature selection methods for the development of a prognostic radiogenomic biomarker in non-small cell lung cancer patientsApurva Singh, Florian A. Hölzl, Sharyn Katz, Despina Kontos. [doi]
• Towards a device-independent deep learning approach for the automated segmentation of sonographic fetal brain structures: a multi-center and multi-device validationAbhi Lad, Adithya Narayan, Hari Shankar, Shefali Jain, Pooja Punjani Vyas, Divya Singh, Nivedita Hegde, Jagruthi Atada, Jens Thang, Saw Shier Nee, Arunkumar Govindarajan, Roopa PS, Muralidhar V. Pai, Akhila Vasudeva, Prathima Radhakrishnan, Sripad Krishna Devalla. [doi]
• Association between DCE MRI background parenchymal enhancement and mammographic texture featuresNatalie M. Baughan, Lindsay Douglas, Maya Ballard, Esther Seoyeon Lee, Alexandra Edwards, Li Lan, Hui Li 0024, Maryellen L. Giger. [doi]
• Visualization and unsupervised clustering of emphysema progression using t-SNE analysis of longitudinal CT images and SNPsHidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Issei Imoto, Yasutaka Nakano, Masahiko Kusumoto, Masahiro Kaneko, Noboru Niki. [doi]
• Multi-modal learning with missing data for cancer diagnosis using histopathological and genomic dataCan Cui 0006, Zuhayr Asad, William F. Dean, Isabelle T. Smith, Christopher Madden, Shunxing Bao, Bennett A. Landman, Joseph T. Roland, Lori A. Coburn, Keith T. Wilson, Jeffrey P. Zwerner, Shilin Zhao, Lee E. Wheless, Yuankai Huo. [doi]
• Detecting COVID-19 from respiratory sound recordings with transformersIdil Aytekin, Onat Dalmaz, Haydar Ankishan, Emine Ulku Saritas, Ulas Bagci, Tolga Çukur, Haydar Celik. [doi]