3 papers
eess.IV2024
CAMP: Continuous and Adaptive Learning Model in Pathology
Anh Tien Nguyen, Keunho Byeon, Kyungeun Kim +3
There exist numerous diagnostic tasks in pathology. Conventional computational pathology formulates and tackles them as independent and individual image classification problems, th…
eess.IV2024
DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images
Ju Cheon Lee, Keunho Byeon, Boram Song +2
In computational pathology, cancer grading has been mainly studied as a categorical classification problem, which does not utilize the ordering nature of cancer grades such as the…
eess.IV2022
GradMix for nuclei segmentation and classification in imbalanced pathology image datasets
Tan Nhu Nhat Doan, Kyungeun Kim, Boram Song +1
An automated segmentation and classification of nuclei is an essential task in digital pathology. The current deep learning-based approaches require a vast amount of annotated data…