Nuclei Segmentation of Fluorescence Microscopy Images Using Three Dimensional Convolutional Neural Networks. - David Joon Ho; Chichen Fu; Paul Salama; Kenneth W. Dunn; Edward J. Delp (CVPR Workshops, 2017)

Nuclei segmentation of fluorescence microscopy images using convolutional neural networks. - Chichen Fu; David Joon Ho; Shuo Han 005; Paul Salama; Kenneth W. Dunn; Edward J. Delp (ISBI, 2017)

Boundary segmentation for fluorescence microscopy using steerable filters. - David Joon Ho; Paul Salama; Kenneth W. Dunn; Edward J. Delp (Image Processing, 2017)

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation. - Chichen Fu; Soonam Lee; David Joon Ho; Shuo Han 005; Paul Salama; Kenneth W. Dunn; Edward J. Delp (CVPR Workshops, 2018)

Person Segmentation Using Convolutional Neural Networks With Dilated Convolutions. - David Joon Ho; Qian Lin 001 (IMAWM, 2018)

Nuclei detection and segmentation of fluorescence microscopy images using three dimensional convolutional neural networks. - David Joon Ho; Chichen Fu; Paul Salama; Kenneth W. Dunn; Edward J. Delp (ISBI, 2018)

Fluorescence Microscopy Image Segmentation Using Convolutional Neural Network With Generative Adversarial Networks. - Chichen Fu; Soonam Lee; David Joon Ho; Shuo Han 005; Paul Salama; Kenneth W. Dunn; Edward J. Delp (CoRR, 2018)

Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images. - David Joon Ho; Shuo Han 005; Chichen Fu; Paul Salama; Kenneth W. Dunn; Edward J. Delp (BHI, 2019)

Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. - David Joon Ho; Narasimhan P. Agaram; Peter J. Schüffler; Chad M. Vanderbilt; Marc-Henri Jean; Meera R. Hameed; Thomas J. Fuchs (MICCAI (5), 2020)

Deep Multi-Magnification Networks for multi-class breast cancer image segmentation. - David Joon Ho; Dig Vijay Kumar Yarlagadda; Timothy M. D'Alfonso; Matthew G. Hanna; Anne Grabenstetter; Peter Ntiamoah; Edi Brogi; Lee K. Tan; Thomas J. Fuchs (Comput. Medical Imaging Graph., 2021)

Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation. - David Joon Ho; M. Herman Chui; Chad M. Vanderbilt; Ji Won Jung; Mark E. Robson; Chan-Sik Park; Jin Roh; Thomas J. Fuchs (CoRR, 2022)

H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma. - Gabriele Campanella; David Joon Ho; Ida Häggström; Anton S. Becker; Jason Chang; Chad M. Vanderbilt; Thomas J. Fuchs (CoRR, 2022)

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction. - David Joon Ho; Narasimhan P. Agaram; Marc-Henri Jean; Stephanie D. Suser; Cynthia Chu; Chad M. Vanderbilt; Paul A. Meyers; Leonard H. Wexler; John H. Healey; Thomas J. Fuchs; Meera R. Hameed (CoRR, 2022)

Stain-invariant self supervised learning for histopathology image analysis. - Alexandre Tiard; Alex Wong 001; David Joon Ho; Yangchao Wu; Eliram Nof; Stefano Soatto; Saad Nadeem (CoRR, 2022)

PAIP 2020: Microsatellite instability prediction in colorectal cancer. - Kyungmo Kim; Kyoungbun Lee; Sungduk Cho; Dong Un Kang; Seongkeun Park; Yunsook Kang; Hyunjeong Kim; Gheeyoung Choe; Kyung Chul Moon; Kyu Sang Lee; Jeong Hwan Park; Choyeon Hong; et al. (Medical Image Anal., 2023)