Fully automated segmentation and classification of renal tumors on CT scans via machine learning

Fully automated segmentation and classification of renal tumors on CT scans via machine learning

Abstract Background To develop and test the performance of a fully automated system for classifying renal tumor subtypes via deep machine learning for automated segmentation and classification. Materials and methods The model was developed using computed tomography (CT) images of pathologically prov...

Full description

Saved in:
Bibliographic Details
Main Authors: Jang Hee Han, Byung Woo Kim, Taek Min Kim, Ji Yeon Ko, Seung Jae Choi, Minho Kang, Sang Youn Kim, Jeong Yeon Cho, Ja Hyeon Ku, Cheol Kwak, Young-Gon Kim, Chang Wook Jeong
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Cancer
Subjects:
CT
Renal cell carcinoma
Radiomics
Machine learning
Deep learning
Segmentation
Online Access:https://doi.org/10.1186/s12885-025-13582-6
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items