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Radiomics--Foundation Fusion for Interpretable RCC Classification: Internal Benchmarking and Exploratory External Transfer

Paper recorded by Signals 4 on 2026-09-22 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23

Category: cs.CV · 计算机视觉 · first seen 2026-09-23

Abstract

Accurate preoperative subtype classification of renal cell carcinoma (RCC) from contrast-enhanced CT remains clinically challenging because clear cell RCC (ccRCC) and non-clear cell RCC often show overlapping imaging appearances. This study evaluates whether foundation representations reduce reliance on handcrafted radiomics, or whether radiomics remains complementary for interpretable tumour char

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#31 most recent of 301 cs.CV papers we have recorded · ↑ newer: GTR: Gated Token Recurrence for Efficient Dense Prediction · ↓ older: VideoGen-Agent: Reinforcing Video Generation Agents
Cite this page: Radiomics--Foundation Fusion for Interpretable RCC Classification: Internal Benchmarking and Exploratory External Transfer: the #31 most recent of 301 cs.CV papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/radiomics-foundation-fusion-for-interpretable-rcc-classification-internal-benchm.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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