The potential of federated learning for self-configuring medical object detection in heterogeneous data distributions

G Rashidi, D Bounias, M Bujotzek, AM Mora, P Neher… - Scientific reports, 2024 - nature.com
Abstract Medical Object Detection (MOD) is a clinically relevant image processing method
that locates structures of interest in radiological image data at object-level using bounding …

TLF: Triple learning framework for intracranial aneurysms segmentation from unreliable labeled CTA scans

L Chai, S Xue, D Tang, J Liu, N Sun, X Liu - Computerized Medical Imaging …, 2024 - Elsevier
Intracranial aneurysm (IA) is a prevalent disease that poses a significant threat to human
health. The use of computed tomography angiography (CTA) as a diagnostic tool for IAs …

[HTML][HTML] Adaptive Noise-Powered Diffusion Model for Efficient and Accurate Object Detection

X Zou, K Han, X Zhang, W Wang, N Wu - Applied Sciences, 2024 - mdpi.com
Recent advancements in object detection, particularly with DiffusionDet, have demonstrated
impressive performance. However, its reliance on numerous random noise-based object …

Unraveling the complexity: deep learning for imbalanced retinal lesion detection and multi-disease identification

G Alfonso-Francia, JC Pedraza-Ortega… - … Modeling Analysis in …, 2023 - Springer
Deep learning (DL) has been widely used to detect abnormalities in retinal image. Typically,
this task has been focused on a specific domain, such as diseases related to glaucoma or …