mlsanityData to 7 Oct 2026

Kidney Recognition in CT Using YOLOv3

arXiv 1910.01268 ↗First posted 3 Oct 2019eess.IV cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

Organ localization can be challenging considering the heterogeneity of medical images and the biological diversity from one individual to another. The contribution of this paper is to overview the performance of the object detection model, YOLOv3, on kidney localization in 2D and in 3D from CT scans. The model obtained a 0.851 Dice score in 2D and 0.742 in 3D. The SSD, a similar state-of-the-art object detection model, showed similar scores on the test set. YOLOv3 and SSD demonstrated the ability to detect kidneys on a wide variety of CT scans including patients suffering from different renal conditions.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 3 Oct 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.