1 citations · 1 across the 8 of their papers we have counts for
8 papers
RaLMPH: Reliability-aware Learning for Multi-Pathologist Harmonization in Whole-Slide Image Classification
Sungrae Hong, Jiwon Jeong, Soeun Cheon +5
Multiple Instance Learning (MIL) is a standard paradigm for Whole-Slide Image (WSI) analysis and has achieved strong results in computational pathology. However, most MIL pipelines…
Perturbative Contrastive Physical Learning
Kyungeun Kim, Amanuel Anteneh, Israel Klich +2
Responses to perturbations are key to understanding physical systems. The ability to contrast such responses by comparing how a system reacts under slightly different conditions pr…
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…
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…
Enhanced extracellular matrix remodeling due to embedded spheroid fluidization
Tao Zhang, Shabeeb Ameen, Sounok Ghosh +5
Tumor spheroids are in vitro three-dimensional, cellular collectives consisting of cancerous cells. Embedding these spheroids in an in vitro fibrous environment, such as a collagen…
A two-dimensional vertex model for curvy cell-cell interfaces at the subcellular scale
Kyungeun Kim, J. M. Schwarz, Martine Ben Amar
Cross-sections of cell shapes in a tissue monolayer typically resemble a tiling of convex polygons. Yet, examples exist where the polygons are not convex with curved cell-cell inte…
Mean field elastic moduli of a three-dimensional cell-based vertex model
Kyungeun Kim, Tao Zhang, J. M. Schwarz
The mechanics of a foam typically depends on the bubble geometry, topology, and the material at hand, be it metallic or polymeric, for example. While the foam energy functional for…
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…