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eess.IV2024
NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning
Saul Fuster, Umay Kiraz, Trygve Eftestøl +2
The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime…
eess.IV2024
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs
Neel Kanwal, Farbod Khoraminia, Umay Kiraz +6
Histopathology is a gold standard for cancer diagnosis under a microscopic examination. However, histological tissue processing procedures result in artifacts, which are ultimately…
eess.IV2023
A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics
Marie Bø-Sande, Edvin Benjaminsen, Neel Kanwal +5
Melanoma is a type of cancer that begins in the cells controlling the pigment of the skin, and it is often referred to as the most dangerous skin cancer. Diagnosing melanoma can be…