Search Results for author: David Joon Ho

Found 7 papers, 3 papers with code

Stain-invariant self supervised learning for histopathology image analysis

1 code implementation14 Nov 2022 Alexandre Tiard, Alex Wong, David Joon Ho, Yangchao Wu, Eliram Nof, Alvin C. Goh, Stefano Soatto, Saad Nadeem

Our method achieves the state-of-the-art performance on several publicly available breast cancer datasets ranging from tumor classification (CAMELYON17) and subtyping (BRACS) to HER2 status classification and treatment response prediction.

Classification Self-Supervised Learning

Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation

1 code implementation28 Mar 2022 David Joon Ho, M. Herman Chui, Chad M. Vanderbilt, Jiwon Jung, Mark E. Robson, Chan-Sik Park, Jin Roh, Thomas J. Fuchs

Instead of annotating all pixels from cancer and non-cancer regions on giga-pixel whole slide images, an iterative process of annotating mislabeled regions from a segmentation model and training/finetuning the model with the additional annotation can reduce the time.

Segmentation whole slide images

Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation

no code implementations29 Oct 2019 David Joon Ho, Dig V. K. Yarlagadda, Timothy M. D'Alfonso, Matthew G. Hanna, Anne Grabenstetter, Peter Ntiamoah, Edi Brogi, Lee K. Tan, Thomas J. Fuchs

Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the completeness of surgical excision and has implications for future treatment.

Decoder Image Segmentation +2

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

no code implementations22 Jan 2018 Chichen Fu, Soonam Lee, David Joon Ho, Shuo Han, Paul Salama, Kenneth W. Dunn, Edward J. Delp

Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue.

Image Generation Segmentation

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