Table of Contents

• Deep neural network for cell type differentiation in myelodysplastic syndrome diagnosis performs similarly when trained on compensated or uncompensated dataJon Camp, Gregory Otteson, Jansen Seheult, Min Shi, Dragan Jevremovic, Horatiu Olteanu, Ahmad Nanaa, Aref Al-Kali, Mohamed Salama, David R. Holmes III. [doi]
• WeakSTIL: weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you needYoni Schirris, Mendel Engelaer, Andreas Panteli, Hugo Mark Horlings, Efstratios Gavves, Jonas Teuwen. [doi]
• Computer extracted features of tumor-infiltrating lymphocytes (TILs) architecture are prognostic of progression-free survival in stage III colon cancerAya Aqeel, Germán Corredor, Vidya Sankar Viswanathan, Chuheng Chen, Mogjan Mokhtari, Pingfu Fu, Joseph E. Willis, Anant Madabhushi. [doi]
• Deformable histopathology-MRI image registration using deep learningYabo Fu, Yang Lei 0002, David M. Schuster, Sagar A. Patel, Jeffrey D. Bradley, Tian Liu 0004, Xiaofeng Yang 0005. [doi]
• Quantitative evaluation of color difference between actual specimens and whole-slide imaging-scanned images calibrated with commercial color chartsYusuke Murayama, Tohru Sugiyama, Yoshihiko Ogino, Hiroki Furuta, Takaaki Kambara, Koi Kamisono, Tokiya Abe, Katsura Emoto, Akinori Hashiguchi, Yoichi Kajimura, Michiie Sakamoto. [doi]
• Tau protein discrete aggregates in Alzheimer's disease: neuritic plaques and tangles detection and segmentation using computational histopathologyKristyna Manousková, Valentin Abadie, Mehdi Ounissi, Gabriel Jimenez 0001, Lev Stimmer, Benoît Delatour, Stanley Durrleman, Daniel Racoceanu. [doi]
• HistoLens: a generalizable tool for increasing accessibility and interpretability of quantitative analyses in digital pathologySamuel P. Border, Brandon Ginley, John E. Tomaszewski, Pinaki Sarder. [doi]
• Automatic tumour segmentation in H&E-stained whole-slide images of the pancreasPierpaolo Vendittelli, Esther M. M. Smeets, Geert J. S. Litjens. [doi]
• Automatic flagging of AI segmentation errors in computational pathologyRakesh Choudhary, Dhadma Balachandran, Jonathan Folmsbee, Jawaria Rahman, Margaret Brandwein-Weber, Scott Doyle. [doi]
• Preserving dense features for Ki67 nuclei detectionSeyed Hossein Mirjahanmardi, Melanie Dawe, Anthony Fyles, Wei Shi, Fei-Fei Liu, Susan Done, April Khademi. [doi]
• Data-efficient and multimodal computational pathologyFaisal Mahmood. [doi]
• Unsupervised super resolution network for hyperspectral histologic imagingLing Ma 0004, Armand Rathgeb, Minh Tran, Baowei Fei. [doi]
• CrowdDeep: deep-learning from the crowd for nuclei segmentationParmida Ghahremani, Arie E. Kaufman. [doi]
• Cell phenotyping using unsupervised clustering on multiplexed fluorescence images of breast cancer tissue specimensWenchao Han, Alison M. Cheung, Dan Wang, Kela Liu, Martin J. Yaffe, Anne L. Martel. [doi]
• Detection of lung cancer metastases in lymph nodes using a multiple instance learning approachMauro Gwerder, Amjad Khan, Christina Neppl, Inti Zlobec. [doi]
• Prediction of tumor mutation burden from H&E whole-slide images: a comparison of training strategies with convolutional neural networksAntong Chen, Tosha Shah, Andrew Brown, Haleh Akrami, Albert Swiston, Amir Vajdi, Radha Krishnan, Razvan Cristescu. [doi]
• Personalized stain style transfer layers for distributed histology classificationYiqing Shen 0003. [doi]
• Self-supervised learning with large-scale web image mining for characterizing glomerular lesionsTianyuan Yao, Yuzhe Lu, Ruining Deng, Zheyu Zhu, Zuhayr Asad, Haichun Yang, Lee E. Wheless, Agnes B. Fogo, Yuankai Huo. [doi]
• Shape-based tumor microenvironment analysis to differentiate non-small cell lung cancer subtypes: a radio-pathomic studySaarthak Kapse, Rajarsi Gupta 0001, Prateek Prasanna. [doi]
• An automated approach for annotating Gleason patterns in whole-mount prostate cancer histology using deep learningMichael Brehler, Allison K. Lowman, Samuel Bobholz, Savannah R. Duenweg, Fitzgerald Kyereme, Cassandra Naze, John Sherman, Kenneth A. Iczkowski, Peter S. LaViolette. [doi]
• Automatic generation of the ground truth for tumor budding using H&E stained slidesThomas E. Tavolara, Arijit Dutta, Martin V. Burks, Wei Chen, Wendy L. Frankel, Metin N. Gurcan, M. Khalid Khan Niazi. [doi]
• A hybrid computational pathology method for the detection of perineural invasion junctionsChang Hee Han, Jin Tae Kwak. [doi]
• Display systems for digital pathology: what are proper luminance, contrast and resolution settings?Varun Vasudev, Albert Xthona, Tom Kimpe. [doi]
• Using deep learning to predict tumor mutational burden in lung squamous cell carcinoma from 20 centersSalma Dammak, Matthew J. Cecchini, Aaron D. Ward. [doi]
• Cancer cell segmentation for cellularity prediction via a weakly labeled/strongly labeled hybrid convolutional neural networkDavid R. Chambers, Bradley B. Brimhall, Donald R. Poole Jr., Edward A. Medina. [doi]
• Automated tubular morphometric visualization for whole kidney biopsyNeil Kavthekar, Brandon Ginley, Samuel P. Border, Nicholas J. Lucarelli, Kuang-Yu Jen, Pinaki Sarder. [doi]
• DUET dual-mode scanning of H&E slides reveals novel contrastFarzad Fereidouni, Richard M. Levenson 0001. [doi]
• Sparse capsule networks for informative representation learning in digital pathologyMatthew McNeil, Cem Anil, Anne L. Martel. [doi]
• Deep learning-enabled classification of gastric ulcers from wireless capsule endoscopic imagesDeepak Bajhaiya, Sujatha Narayanan Unni. [doi]
• Inpainting missing tissue in multiplexed immunofluorescence imagingShunxing Bao, Yucheng Tang, Ho Hin Lee, Riqiang Gao, Qi Yang 0004, Xin Yu 0002, Sophie Chiron, Lori A. Coburn, Keith T. Wilson, Joseph T. Roland, Bennett A. Landman, Yuankai Huo. [doi]
• Weakly supervised histopathological image representation learning based on contrastive dynamic clusteringJun Li 0106, Zhiguo Jiang, Yushan Zheng, Haopeng Zhang 0001, Jun Shi, Dingyi Hu, Wei Luo, Zhongmin Jiang, Chenghai Xue. [doi]
• Identifying the origination of liver metastasis using a hand-crafted computational pathology approachChuheng Chen, Cheng Lu 0001, Joseph E. Willis, Anant Madabhushi. [doi]
• Predicting HER2 scores from registered HER2 and H&E imagesThomas E. Tavolara, M. Khalid Khan Niazi, Gary Tozbikian, Robert Wesolowski, Metin N. Gurcan. [doi]
• Eosinophilic esophagitis multi-label feature recognition on whole slide imaging using transfer learningYuxuan Shi, Quan Liu, Jiachen Xu, Zuhayr Asad, Can Cui 0006, Hernán Correa, Yash Choksi, Girish Hiremath, Yuankai Huo. [doi]
• A deep learning-based computational prediction model for characterizing cellular biomarker distribution in tumor microenvironmentZhengyao Peng, Chang Bian, Yang Du, Jie Tian 0001. [doi]
• Deep ordinal regression for automatic tumor cellularity assessment from pathological imagesBi Song, Albert Huang, Ming-Chang Liu. [doi]
• A cloud-based tool for federated segmentation of whole slide imagesBrendon Lutnick, David Manthey, Jan U. Becker, Jonathan E. Zuckerman, Luis Rodrigues, Kuang-Yu Jen, Pinaki Sarder. [doi]
• Anonymising pathology data using generative adversarial networksDavid Morrison, David Harris-Birtill. [doi]
• Quantitative histomorphometric features of tumor nuclei are prognostic of disease-free survival in papillary thyroid carcinomaShayan Monabbati, Paula Toro, Kaustav Bera, Pingfu Fu, Sylvia A. Lou, Anant Madabhushi. [doi]
• Survival time prediction from unannotated lung cancer histopathology imagesNikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath. [doi]
• Muti-stage attention-based network for brain tumor subtype classificationSudhir Suman, Prateek Prasanna. [doi]
• Investigating intra-tumor heterogeneity in non-small cell lung cancer using multiplexed immunohistochemistry and deep learningKouther Noureddine, Paul Gallagher, Griffin Thomas, Sylvia Lam, Gavin MacAulay, Anna McGuire, John English, Martial Guillaud, Calum MacAulay. [doi]
• Dense multi-object 3D glomerular reconstruction and quantification on 2D serial section whole slide imagesRuining Deng, Haichun Yang, Zuhayr Asad, Zheyu Zhu, Shiru Wang, Lee E. Wheless, Agnes B. Fogo, Yuankai Huo. [doi]
• Group affinity weakly supervised segmentation from prior selected tissue in colorectal histopathology imagesHuu-Giao Nguyen, Amjad Khan, Heather Dawson, Alessandro Lugli, Inti Zlobec. [doi]
• Procedural generation of synthetic multiplex immunohistochemistry images using cell-based image compression and conditional generative adversarial networksLaurin Herbsthofer, Barbara Ehall, Martina Tomberger, Barbara Prietl, Thomas R. Pieber, Pablo López-García. [doi]
• Selecting training samples for ovarian cancer classification via a semi-supervised clustering approachJennifer Salguero López, Prateek Prasanna, Germán Corredor, Angel Cruz-Roa, David Becerra, Eduardo Romero 0001. [doi]
• Front Matter: Volume 12039 [doi]
• RAE-Net: a deep learning system for staging of estrous cycleDigant Patel, Pranab Samanta, Ravi Kamble, Nitin Singhal. [doi]
• Spatial analysis of cellular arrangement using quantitative, single-cell imaging of protein multiplexingAlison M. Cheung, Dan Wang, Kela Liu, Sarah Hynes, Ben Wang, Simone Stone, Pamela Ohashi, Martin J. Yaffe. [doi]
• Computational integration of renal histology and urinary proteomics using neural networksNicholas J. Lucarelli, Donghwan Yun, Dohyun Han, Brandon Ginley, Kyung Chul Moon, Avi Rosenberg, John Tomaszewski 0001, Seung Seok Han, Pinaki Sarder. [doi]
• Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and deep learningXiming Zhou, Ling Ma 0004, Hasan K. Mubarak, James V. Little, Amy Y. Chen, Larry L. Myers, Baran D. Sumer, Baowei Fei. [doi]
• Deep learning-based integration of histology, radiology, and genomics for improved survival prediction in glioma patientsLuoting Zhuang, Jana Lipková, Richard Chen 0001, Faisal Mahmood. [doi]
• FIBI: a direct-to-digital microscopy approach for slide-free histologyFarzad Fereidouni, Taryn Morningstar, Alexander Borowsky, Richard M. Levenson 0001. [doi]
• Thyroid carcinoma detection on whole histologic slides using hyperspectral imaging and deep learningMinh Ha Tran, Ling Ma 0004, James V. Litter, Amy Y. Chen, Baowei Fei. [doi]
• CellSegNet: an adaptive multi-resolution hybrid network for cell segmentationJunwei Deng, Yiqing Shen 0003, Yi Guo 0001, Jing Ke. [doi]
• A hierarchical deep learning approach for segmentation of glioblastoma tumor niches on digital histopathologyAlvaro Sandino Garzon, Ruchika Verma, Yijang Chen, David Becerra Tovar, Eduardo Romero Castro, Pallavi Tiwari. [doi]
• Cloud-based platform for human-in-the-loop re-annotation of whole slide imaging: large scale semantic pathology segmentationJonathan Folmsbee, Scott Doyle, Rakesh Choudhary, Margaret Brandwein-Weber, Jawaria Rahman. [doi]
• Histopathological image classification based on self-supervised vision transformer and weak labelsAhmet Gokberk Gul, Özdemir Çetin, Christoph Reich, Nadine Flinner, Tim Prangemeier, Heinz Koeppl. [doi]
• In the use of artificial intelligence and hyperspectral imaging in digital pathology for breast cancer cell identificationLaura Quintana, Samuel Ortega, Raquel León, Himar Fabelo, Francisco Javier Balea-Fernández, Esther Sauras, Marylène Lejeune, Ramón Bosch, Carlos López 0002, Gustavo M. Callicó. [doi]
• Integrating image analysis with single cell RNA-seq data to study podocyte-specific changes in diabetic kidney diseaseDarshana Govind, Saber Meamardoost, Rabi Yacoub, Rudiyanto Gunawan, John E. Tomaszewski, Pinaki Sarder. [doi]