From the 1 of 8 linked papers with an AI index.
8 papers
Causal-Adversarial Probing of Clinical Covariates for Prostate MRI Grading
Yipei Wang, Shiqi Huang, Wen Yan +6
The paper introduces an adversarial causal‑reasoning framework to identify which clinical covariates help or hinder deep‑learning models for prostate MRI cancer grading, showing th…
Reasoning in machine vision by learning fast and slow thinking
Shaheer U. Saeed, Yipei Wang, Veeru Kasivisvanathan +4
Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence remains bound to training data,…
Deep EM with Hierarchical Latent Label Modelling for Multi-Site Prostate Lesion Segmentation
Wen Yan, Yipei Wang, Shiqi Huang +5
Label variability is a major challenge for prostate lesion segmentation. In multi-site datasets, annotations often reflect centre-specific contouring protocols, causing segmentatio…
Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging
Weixi Yi, Yipei Wang, Wen Yan +10
Multiparametric MRI is increasingly recommended as a first-line noninvasive approach to detect and localize prostate cancer, requiring at minimum diffusion-weighted (DWI) and T2-we…
ProFound: A moderate-sized vision foundation model for multi-task prostate imaging
Yipei Wang, Yinsong Xu, Weixi Yi +11
Many diagnostic and therapeutic clinical tasks for prostate cancer increasingly rely on multi-parametric MRI. Automating these tasks is challenging because they necessitate expert…
Retrieving Patient-Specific Radiomic Feature Sets for Transparent Knee MRI Assessment
Yaxi Chen, Simin Ni, Jingjing Zhang +7
Classical radiomic features are designed to quantify image appearance and intensity patterns. Compared with end-to-end deep learning (DL) models trained for disease classification,…