Table of Contents

• Transferring CT image biomarkers from fibrosing idiopathic interstitial pneumonia to COVID-19 analysisCatalin I. Fetita, Simon Rennotte, Marjorie Latrasse, Ruxandra Tapu, Mathilde Maury, Bogdan Mocanu, Hilario Nunes, Pierre-Yves Brillet. [doi]
• Radiomic texture analysis for the assessment of osteoporosis on low-dose thoracic CT scansJordan D. Fuhrman, Linnea Kremer, Yeqing Zhu, Rowena Yip, Feng Li, Li Lan, Hui Li 0024, Artit C. Jirapatnakul, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger. [doi]
• Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findingsConnor Cowan, Joseph Bae, Gagandeep Singh, Rohit Khullar, Shrey Shah, Nikhil Madan, Prateek Prasanna. [doi]
• Deep attention mask regional convolutional neural network for head-and-neck MRI multi-organ auto-delineationXianjin Dai, Yang Lei 0002, Tonghe Wang, Jun Zhou, Walter J. Curran, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Photographic cranial shape analysis using deep learningMohammad Ali Yektaie, Zahra Ghasemi, S. Hossein Hezaveh, Fereshteh Aalamifar, Reza Seifabadi, Marius George Linguraru. [doi]
• Automated multi-channel segmentation for the 4D myocardial velocity mapping cardiac MRYinzhe Wu 0001, Suzan Hatipoglu, Diego Alonso-Álvarez, Peter Gatehouse, David N. Firmin, Jennifer Keegan, Guang Yang 0006. [doi]
• Estimating near term breast cancer risk from sequential mammograms using deep learning, radon cumulative distribution transform, and a clinical risk factor: preliminary analysisJuhun Lee, Robert M. Nishikawa, Andriy Bandos, Margarita L. Zuley. [doi]
• Traction bronchiectasis identification and quantitative biomarkers for follow-up in nonspecific interstitial pneumoniaMarjorie Latrasse, Simon Rennotte, Pierre-Yves Brillet, Sylvain Marchand-Adam, Catalin I. Fetita. [doi]
• Deep learning analysis on raw image data: case study on holographic cell analysisGal Gozes, Shani Ben Baruch, Noa Rotman-Nativ, Darina Roitshtain, Natan T. Shaked, Hayit Greenspan. [doi]
• Deep neural networks trained for segmentation are sensitive to brightness changes: preliminary resultsZhe Zhu, Mustafa R. Bashir, Maciej A. Mazurowski. [doi]
• Segmentation of the thoracic aorta using an attention-gated U-NetJiayang Zhong, Zhangxing Bian, Charles R. Hatt, Nicholas S. Burris. [doi]
• Applying a new feature fusion method to classify breast lesionsNajmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan, Sam Teymoori. [doi]
• Multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography with and without computerized decision supportLubomir M. Hadjiiski, Monika Joshi, Ajjai Alva, Heang-Ping Chan, Richard H. Cohan, Elaine M. Caoili, Galina Kirova-Nedyalkova, Matthew S. Davenport, Prasad R. Shankar, Isaac R. Francis, Kenny H. Cha, Ravi K. Samala, Phillip L. Palmbos, Alon Z. Weizer. [doi]
• Intensity normalization of prostate MRIs using conditional generative adversarial networks for cancer detectionThomas DeSilvio, Stefania Moroianu, Indrani Bhattacharya, Arun Seetharaman, Geoffrey A. Sonn, Mirabela Rusu. [doi]
• A general fully automated deep-learning method to detect cardiomegaly in chest x-raysJosé Raniery Ferreira Jr., Diego Armando Cardona Cárdenas, Ramon Alfredo Moreno, Marina de Fátima de Sá Rebelo, José Eduardo Krieger, Marco Antonio Gutierrez 0001. [doi]
• Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during mechanical thrombectomyMohammad Mahdi Shiraz Bhurwani, Kenneth V. Snyder, Mohammad Waqas, Maxim Mokin, Ryan A. Rava, Alexander R. Podgorsak, Kelsey N. Sommer, Jason M. Davies, Elad I. Levy, Adnan H. Siddiqui, Ciprian N. Ionita. [doi]
• Comparison of 2D and 3D U-Net breast lesion segmentations on DCE-MRIRoma Bhattacharjee, Lindsay Douglas, Karen Drukker, Qiyuan Hu, Jordan D. Fuhrman, Deepa Sheth, Maryellen L. Giger. [doi]
• Automatic segmentation of the structures in the nasal cavity and the ethmoidal sinus for the quantification of nasal septal deviationsCristina Oyarzun Laura, Katrin Hartwig, Alexander Distergoft, Tim Hoffmann, Kathrin Scheckenbach, Melanie Brüsseler, Stefan Wesarg. [doi]
• Differentiation of Parkinson's disease and non-Parkinsonian olfactory dysfunction with structural MRI dataJie Mei, Cécilia Tremblay, Nikola Stikov, Christian Desrosiers, Johannes Frasnelli. [doi]
• Role of standard and soft tissue chest radiography images in COVID-19 diagnosis using deep learningQiyuan Hu, Karen Drukker, Maryellen L. Giger. [doi]
• Fully automated segmentation of brain tumor from multiparametric MRI using 3D context U-Net with deep supervisionMingquan Lin, Shadab Momin, Boran Zhou, Katherine Tang, Yang Lei 0002, Walter J. Curran, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Renal parenchyma segmentation in abdominal MR images based on cascaded deep convolutional neural network with signal intensity correctionHyeonjin Kim, Helen Hong, Dae Chul Jung, Kidon Chang, Koon Ho Rha. [doi]
• An improved mammography malignancy model with self-supervised learningYen Nhi Truong Vu, Trevor Tsue, Jason Su, Sadanand Singh. [doi]
• Deformable MRI-CT liver image registration using convolutional neural network with modality independent neighborhood descriptorsYabo Fu, Yang Lei 0002, Tonghe Wang, Jun Zhou, Walter J. Curran, Pretesh Patel, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Machine-learning-based clinical plaque detection using a synthetic plaque lesion model for coronary CTANikolas Schnellbächer, Haissam Ragab, Hannes Nickisch, Tobias Wissel, Clemens Spink, Gunnar Lund, Michael Grass 0001. [doi]
• Sparse analysis of deep features for characterization of breast massesSokratis Makrogiannis, Keni Zheng, Chelsea Harris. [doi]
• Radiomic features predict local failure-free survival in stage III NSCLC adenocarcinoma treated with chemoradiationJosé-Marcio Luna, Andrew R. Barsky, Russell T. Shinohara, Alexandra D. Dreyfuss, Leonid Roshkovan, Michelle Hershman, Babak Haghighi, Bardia Yousefi, Peter B. Noël, Keith A. Cengel, Sharyn Katz, Eric S. Diffenderfer, Despina Kontos. [doi]
• Parenchymal field effect analysis for breast cancer risk assessment: evaluation of FFDM radiomic similarityNatalie M. Baughan, Hui Li 0024, Li Lan, Chun-Wai Chan, Matthew Embury, Gary Whitman, Randa El-Zein, Isabelle Bedrosian, Maryellen L. Giger. [doi]
• COVID-19 opacity segmentation in chest CT via HydraNet: a joint learning multi-decoder networkNimrod Sagie, Shiri Almog, Ayelet Talby, Hayit Greenspan. [doi]
• Tooth recognition and classification using multi-task learning and post-processing in dental panoramic radiographsTakumi Morishita, Chisako Muramatsu, Xiangrong Zhou, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Takeshi Hara, Yoshiko Ariji, Eiichiro Ariji, Akitoshi Katsumata, Hiroshi Fujita 0001. [doi]
• Modality agnostic intracranial aneurysm detection through supervised vascular surface classificationZiga Bizjak, Bostjan Likar, Franjo Pernus, Ziga Spiclin. [doi]
• Ovarian assessment using deep learning-based 3D ultrasound super resolutionSaumya Gupta, Venkata Suryanarayana K., Srinivas Rao Kudavelly, G. A. Ramaraju. [doi]
• Applying quantitative image markers to predict clinical measures after aneurysmal subarachnoid hemorrhageGopichandh Danala, Masoom Desai, Maryum Shoukat, Ahmer Asif, Morteza Heidari, Bin Zheng 0001. [doi]
• Automatic fetal presentation diagnosis from ultrasound images for rural zones: head location as an indicator for fetal presentationJunior Arroyo, Ana Cecilia Saavedra, Lorena Tamayo, Miguel Egoavil, Berta Ramos, Benjamín Castañeda. [doi]
• Multi-resolution deep network ensembles for cervical intervertebral disc segmentation are biased by trainerIen Li, Kirstin Cook, Michael Le, Bilwaj Gaonkar, Luke Macyszyn. [doi]
• Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networksYuichiro Hayashi, Masahiro Oda, Chen Shen 0002, Masahiro Hashimoto, Yoshito Otake, Toshiaki Akashi, Kensaku Mori. [doi]
• Improved segmentation by adversarial U-NetDavid Sriker, Dana Cohen 0002, Noa Cahan, Hayit Greenspan. [doi]
• Unsupervised survival prediction model from CT images of patients with COVID-19Tomoki Uemura, Janne J. Näppi, Chinatsu Watari, Tohru Kamiya, Hiroyuki Yoshida. [doi]
• Classification of schizophrenia from functional MRI using large-scale extended Granger causalityAxel Wismüller, M. Ali Vosoughi. [doi]
• Severity assessment of COVID-19 using imaging descriptors: a deep-learning transfer learning approach from non-COVID-19 pneumoniaRavi K. Samala, Lubomir M. Hadjiiski, Heang-Ping Chan, Chuan Zhou 0002, Jadranka Stojanovska, Prachi Pragya Agarwal, Christopher Fung. [doi]
• Case-based diagnostic classification repeatability using radiomic features extracted from full-field digital mammography images of breast lesionsPaul Amstutz, Karen Drukker, Hui Li 0024, Hiroyuki Abe, Maryellen L. Giger, Heather M. Whitney. [doi]
• Electronic removal of lesions for more robust BPE scoring on breast DCE-MRILindsay Douglas, Deepa Sheth, Maryellen L. Giger. [doi]
• Assessment of bone fragility in projection images using radiomic featuresQian Cao, Nicholas Petrick, Stephanie Coquia, Kenny H. Cha, Rongping Zeng, Keith Wear, Berkman Sahiner, Qin Li 0018. [doi]
• Triplet network for classification of benign and pre-malignant polypsRoger Fonolla, Maciej Smyl, Fons van der Sommen, Ramon-Michel Schreuder, Erik J. Schoon, Peter H. N. de With. [doi]
• How to select training data to segment mammary gland region using a deep-learning approach for reliable individualized screening mammographyMika Yamamuro, Yoshiyuki Asai, Naomi Hashimoto, Nao Yasuda, Takahiro Yamada, Mitsutaka Nemoto, Yuichi Kimura, Hisashi Handa, Hisashi Yoshida, Koji Abe, Masahiro Tada, Hitoshi Habe, Takashi Nagaoka, Yoshiaki Ozaki, Seiun Nin, Kazunari Ishii, Yongbum Lee. [doi]
• Deep learning-based risk stratification for treatment management of multiple myeloma with sequential MRI scansChuan Zhou 0002, Heang-Ping Chan, Lubomir M. Hadjiiski, Qian Dong. [doi]
• Abdominal CT urography kidney segmentation using spatiotemporal fully convolutional networkWankang Zeng, Wenkang Fan, Zhuohui Zheng, Rong Chen, Song Zheng, Jianhui Chen, Rong Liu, Zengqin Liu, Yinran Chen, Xiongbiao Luo. [doi]
• Medical knowledge-guided deep curriculum learning for elbow fracture diagnosis from x-ray imagesJun Luo 0010, Gene Kitamura, Emine Doganay, Dooman Arefan, Shandong Wu. [doi]
• Multi-task learning to incorporate clinical knowledge into deep learning for breast cancer diagnosisGiacomo Nebbia, Dooman Arefan, Margarita L. Zuley, Jules H. Sumkin, Shandong Wu. [doi]
• Lung infection and normal region segmentation from CT volumes of COVID-19 casesMasahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Kensaku Mori. [doi]
• Detection of left bundle branch block and obstructive coronary artery disease from myocardial perfusion scintigraphy using deep neural networksIda Arvidsson, Niels Christian Overgaard, Anette Davidsson, Jeronimo Frias Rose, Kalle Åström, Miguel Ochoa Figueroa, Anders Heyden. [doi]
• Multiview and multiclass image segmentation using deep learning in fetal echocardiographyKen C. L. Wong, Elena S. Sinkovskaya, Alfred Z. Abuhamad, Tanveer F. Syeda-Mahmood. [doi]
• Improving retinal images segmentation using styleGAN image augmentationGal Ofir, Dana Cohen. [doi]
• Modifying U-Net for small dataset: a simplified U-Net version for liver parenchyma segmentationPravda Jith Ray Prasad, Ole Jakob Elle, Frank Lindseth, Fritz Albregtsen, Rahul Prasanna Kumar. [doi]
• CoroNet: a deep network architecture for enhanced identification of COVID-19 from chest x-ray imagesChirag Agarwal, Shahin Khobahi, Dan Schonfeld, Mojtaba Soltanalian. [doi]
• Early detection of at-risk keratoplasties and prediction of future corneal graft rejection from pre-diagnosis endothelial cell imagesNaomi Joseph, Beth A. Benetz, Harry J. Menegay, Silke Oellerich, Lamis Baydoun, Gerrit Melles, Jonathan H. Lass, David L. Wilson. [doi]
• Deep learning-based deformable MRI-CBCT registration of male pelvic regionShadab Momin, Yang Lei 0002, Tonghe Wang, Yabo Fu, Pretesh Patel, Ashesh B. Jani, Walter J. Curran, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Deep learning-based lesion segmentation in paediatric epilepsyAzad Aminpour, Mehran Ebrahimi, Elysa Widjaja. [doi]
• Decoding Radiology: A Brief HistorySaurabh Jha. [doi]
• Self-training with improved regularization for sample-efficient chest x-ray classificationDeepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap. [doi]
• 3D U-net for registration of lung nodules in longitudinal CT scansAryan Ghazipour, Benjamin Veasey, Albert Seow, Amir A. Amini. [doi]
• Region of interest discovery using discriminative concrete autoencoder for COVID-19 lung CT imagesYupei Zhang, Yang Lei 0002, Mingquan Lin, Walter J. Curran, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• MRI-based prostate and dominant lesion segmentation using deep neural networkTonghe Wang, Yang Lei 0002, Olayinka A. Abiodun Ojo, Oladunni A. Akin-Akintayo, Akinyemi A. Akintayo, Walter J. Curran, Tian Liu 0004, David M. Schuster, Xiaofeng Yang 0005. [doi]
• Comparison between threshold-based and deep learning-based bone segmentation on whole-body CT imagesNoémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Pascal Jézéquel, Mario Campone, Nicolas Normand, Mathieu Rubeaux. [doi]
• Intestinal region reconstruction of ileus cases from 3D CT images based on graphical representation and its visualizationHirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Yudai Tamada, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori. [doi]
• RV strain classification from 3D CTPA scans using weakly supervised residual attention modelNoa Cahan, Edith M. Marom, Shelly Soffer, Yiftach Barash, Eli Konen, Eyal Klang, Hayit Greenspan. [doi]
• 3D deep learning for computer-aided detection of serrated polyps in CT colonographyJanne J. Näppi, Tomoki Uemura, Perry J. Pickhardt, David H. Kim, Hiroyuki Yoshida. [doi]
• Intrinsic radiomics phenotypes of DCI from breast DCE-MRI: demonstrating feasibility in interim analysis of the ECOG-ACRIN E4112 trialVivian Belenky, Rhea Chitalia, Nickolas Lewis, Debosmita Biswas, Constantine Gatsonis, Jennifer Xiao, Michael Hirano, Sunil Badve, Joseph A. Sparano, Seema Khan, Kathy D. Miller, Constance Lehman, Justin Romanoff, Antonio C. Wolff, Christopher Comstock, Savannah C. Partridge, Habib Rahbar, Despina Kontos. [doi]
• Classification of COVID-19 in chest radiographs: assessing the impact of imaging parameters using clinical and simulated imagesRafael B. Fricks, Ehsan Abadi, Francesco Ria, Ehsan Samei. [doi]
• Two-stage meniscus segmentation framework integrating multiclass localization network and adversarial learning-based segmentation network in knee MR imagesUju Jeon, Hyeonjin Kim, Helen Hong, Joon-Ho Wang. [doi]
• Reinforced learning from serial CT to improve the early diagnosis of lung cancer in screeningYifan Wang, Chuan Zhou 0002, Lei Ying, Heang-Ping Chan, Lubomir M. Hadjiiski, Aamer Chughtai, Ella A. Kazerooni. [doi]
• COVID-19 pneumonia diagnosis using chest x-ray radiograph and deep learningDalton Griner, Ran Zhang 0009, Xin Tie, Chengzhu Zhang, John W. Garrett, Ke Li, Guang-Hong Chen. [doi]
• Extremely imbalanced subarachnoid hemorrhage detection based on DenseNet-LSTM network with class-balanced loss and transfer learningZhongyang Lu, Masahiro Oda, Yuichiro Hayashi, Tao Hu, Hayato Itoh, Takeyuki Watadani, Osamu Abe, Masahiro Hashimoto, Masahiro Jinzaki, Kensaku Mori. [doi]
• A hybrid approach for mammary gland segmentation on CT images by embedding visual explanations from a deep learning classifier into a Bayesian inferenceXiangrong Zhou, Seiya Yamagishi, Takeshi Hara, Hiroshi Fujita 0001. [doi]
• Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral imagesKa'Toria Edwards, Martin T. Halicek, James V. Little, Amy Y. Chen, Baowei Fei. [doi]
• Dense-layer-based YOLO-v3 for detection and localization of colon perforationsKai Jiang, Hayato Itoh, Masahiro Oda, Taishi Okumura, Yuichi Mori, Masashi Misawa, Takemasa Hayashi, Shin-ei Kudo, Kensaku Mori. [doi]
• Overcoming the "catastrophic forgetting" effect in transfer learning to achieve vendor independent performance for the COVID-19 pneumonia classification task using chest x-ray radiographsRan Zhang 0009, Guang-Hong Chen. [doi]
• Lung nodule malignancy prediction in chest CT scans based on a CNN model with auxiliary task learningXiaomeng Gu, Fucai Chen, Weiyang Xie, Jun Zhao, Qiang Li. [doi]
• Deep radiomics: deep learning on radiomics texture imagesRahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof. [doi]
• Detecting invasive breast carcinoma on dynamic contrast-enhanced MRIStefania L. Moroianu, Mirabela Rusu. [doi]
• Development of a radiogenomic biomarker for tumor characterization and prognosis in non-small cell lung cancer patientsApurva Singh, Zhuoyang Wang, Sharyn Katz, Bardia Yousefi, Despina Kontos. [doi]
• A system for fully automated monitoring of lesion evolution over time in multiple sclerosisSven Kuckertz, Florian Weiler, Britta Matusche, Carsten Lukas, Lothar Spies, Jan Klein 0001, Stefan Heldmann. [doi]
• Tissue-border detection in volumetric laser endomicroscopy using bi-directional gated recurrent neural networksSanne E. Okel, Fons van der Sommen, Endi Selmanaj, Joost van der Putten, Maarten R. Struyvenberg, Jacques J. G. H. M. Bergman, Peter H. N. de With. [doi]
• An automatic diagnosis of idiopathic pulmonary fibrosis (IPF) using domain knowledge-guided attention models in HRCT imagesWenxi Yu, Hua Zhou 0001, Youngwon Choi, Jonathan G. Goldin, Pangyu Teng, Hyun J. Grace Kim. [doi]
• 3-D multitask deep neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusionHoang-Long Le, Yejin Jeon, Hong Gee Roh, Hyun-Jeong Kim, Jin Tae Kwak. [doi]
• Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS)Yin Xi, Maysam Shahedi, Quyen N. Do, James D. Dormer, Matthew A. Lewis, Baowei Fei, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler. [doi]
• Deep learning-based aggressive progression prediction from CT images of hepatocellular carcinomaMeiqing Pan, Zhenchao Tang, Sirui Fu, Wei Mu, Jie Zhang, Xiaoqun Li, Hui Zhang, Ligong Lu, Jie Tian 0001. [doi]
• Otoscopy video screening with deep anomaly detectionWeiyao Wang 0002, Aniruddha Tamhane, John R. Rzasa, James H. Clark 0004, Therese L. Canares, Mathias Unberath. [doi]
• Clinically significant prostate cancer detection on MRI with self-supervised learning using image context restorationAmir Bolous, Arun Seetharaman, Indrani Bhattacharya, Richard E. Fan, Simon John Christoph Soerensen, Leo C. Chen, Pejman Ghanouni, Geoffrey A. Sonn, Mirabela Rusu. [doi]
• Architectural distortion detection in digital breast tomosynthesis with adaptive receptive field and adaptive convolution kernel shapeYue Li, Zilong He, Xiangyuan Ma, Weimin Xu, Chanjuan Wen, Hui Zeng, Weixiong Zeng, Zeqi Wu, Genggeng Qin, Weiguo Chen, Yao Lu 0007. [doi]
• Multi-scale view-based convolutional neural network for breast cancer classification in ultrasound imagesHui Meng, Qingfeng Li, Xuefeng Liu, Yong Wang, Jianwei Niu 0002. [doi]
• Automatic localization of lung opacity in chest CT images: a real-world studyYiting Xie, Deepta Rajan, Larissa C. Schudlo, Yusuke Takeuchi, Benedikt Graf, Adam Coy, Mohammadreza Negahdar, Vandana V. Mukherjee, David Beymer, Arun Krishnan. [doi]
• Spatial matching of magnified 2D mammography images and specimen radiographs: towards improved characterization of suspicious microcalcificationsNoor Nakhaei, Chrysostomos Marasinou, Akinyinka Omigbodun, Nina Capiro, Bo Li, Anne Hoyt, William Hsu. [doi]
• Quantitative assessment of deformational plagiocephaly and brachycephaly at the point-of-careReza Seifabadi, Fereshteh Aalamifar, S. Hossein Hezaveh, Can Kocabalkanli, Marius George Liguraru. [doi]
• Automatic detection of ellipsoid zone loss due to Hydroxychloroquine retinal toxicity from SD-OCT imagingTharindu S. De Silva, Gopal Jayakar, Peyton Grisso, Emily Y. Chew, Nathan Hotaling, Catherine A. Cukras. [doi]
• Fluorescence lifetime imaging endomicroscopy-based ex-vivo lung cancer prediction using multi-scale concatenated-dilation convolutional neural networksQiang Wang 0028, James R. Hopgood, Marta Vallejo. [doi]
• Detecting COVID-19 infected pneumonia from x-ray images using a deep learning model with image preprocessing algorithmMorteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu, Bin Zheng 0001. [doi]
• Video-based infant monitoring using a CNN-LSTM schemeLan Min, Yue Sun, Peter H. N. de With. [doi]
• Probabilistic segmentation of small metastatic brain tumors using liquid state machine ensembleAndrew Elliott, Cole Morgan, Carlo Torres, Caroline Chung. [doi]
• A novel feature reduction method to improve performance of machine learning modelSeyedehnafiseh Mirniaharikandehei, Morteza Heidari, Gopichandh Danala, Sivaramakrishnan Lakshmivarahan, Bin Zheng 0001. [doi]
• Multi-task learning of perceptive feature for thyroid malignant probability predictionZixiong Gao, Yufan Chen, Wuping Mai, Yao Lu 0007, Shuyu Wu, Hongmei Liu. [doi]
• Panoptic segmentation of wounds in a pig modelThomas E. Tavolara, Adam M. Jorgensen, Metin N. Gurcan, Sean V. Murphy, M. Khalid Khan Niazi. [doi]
• Fully automatic bone segmentation through contrast enhanced torso CT datasetAhmed S. Maklad, Hassan Hashem, Mikio Matsuhiro, Hidenobu Suzuki, Noboru Niki. [doi]