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Found 5 papers, 2 papers with code
Position Paper: Building Trust in Synthetic Data for Clinical AI
Deep generative models and synthetic medical data have shown significant promise in addressing key challenges in healthcare, such as privacy concerns, data bias, and the scarcity of realistic datasets.
Early Detection of Retinopathy of Prematurity stage using Deep Learning approach
The system was tested on 45 images and reached detection accuracy of 0. 88, showing that deep learning detection with pre-processing by image normalization allows robust detection of ROP in early stages.
Style Transfer based Coronary Artery Segmentation in X-ray Angiogram
A deep learning-based edge adaptive instance normalization style transfer technique for segmenting the coronary arteries, is presented in this paper.
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf. io/nqjyw/, https://osf. io/t98fz/).
Deep Residual Network based Automatic Image Grading for Diabetic Macular Edema
Diabetic Macular Edema (DME) is an advanced symptom of diabetic retinopathy that affects central vision of diabetes patients.
Ranked #1 on
Medical Image Classification
on IDRiD
(Accuracy (% ) metric)
