Automated Kidney Tumor Classification

The study was reviewed and approved by Ethics Committee of the Affiliated Hospital of Southwest Medical University (18 January 2017, KY2021023). CT data were retrieved from the 2019 Kidney and Kidney Tumor Segmentation Challenge (KiTS19) (https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=61081171) of The Cancer Imaging Archive (TCIA) open access database. Arterial phase-enhanced images of 210 patients from the database were used to establish an automatic classification model. The kidneys and tumors were already manually segmented. These CT images were randomly divided into a training set (168 cases) and test set (42 cases).

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Li Y., Gao X., Tang X., Lin S, & Pang H. (2023). Research on automatic classification technology of kidney tumor and normal kidney tissue based on computed tomography radiomics. Frontiers in Oncology, 13, 1013085.

Publication 2023

Arterial Cancer Hospital ethics committee Kidney tumor Kidneys Patients Tumors

Corresponding Organization :

Other organizations : Affiliated Hospital of Southwest Medical University

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Variable analysis

independent variables

None explicitly mentioned

dependent variables

Automatic classification model for kidneys and tumors

control variables

Manually segmented kidneys and tumors in the CT images
Arterial phase-enhanced CT images of 210 patients
Random division of the CT images into a training set (168 cases) and test set (42 cases)

controls

No positive or negative controls were explicitly mentioned in the input protocol.

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