Feb. 12, 2024, 5:46 a.m. | Guoyang Xie Jinbao Wang Yawen Huang Jiayi Lyu Feng Zheng Yefeng Zheng Yaochu Jin

cs.CV updates on arXiv.org arxiv.org

The problem of how to assess cross-modality medical image synthesis has been largely unexplored. The most used measures like PSNR and SSIM focus on analyzing the structural features but neglect the crucial lesion location and fundamental k-space speciality of medical images. To overcome this problem, we propose a new metric K-CROSS to spur progress on this challenging problem. Specifically, K-CROSS uses a pre-trained multi-modality segmentation network to predict the lesion location, together with a tumor encoder for representing features, such …

assessment cs.cv eess.iv features focus image images location medical quality space synthesis synthesized

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

Lead Software Engineer, Machine Learning

@ Monarch Money | Remote (US)

Investigator, Data Science

@ GSK | Stevenage

Alternance - Assistant.e Chef de Projet Data Business Intelligence (H/F)

@ Pernod Ricard | FR - Paris - The Island

Expert produit Big Data & Data Science - Services Publics - Nantes

@ Sopra Steria | Nantes, France