Out-of-distribution detection in medical image analysis: A survey
Computer-aided diagnostics has benefited from the development of deep learning-based
computer vision techniques in these years. Traditional supervised deep learning methods …
computer vision techniques in these years. Traditional supervised deep learning methods …
Toward Foundation Models in Radiology? Quantitative Assessment of GPT-4V's Multimodal and Multianatomic Region Capabilities
QD Strotzer, F Nieberle, LS Kupke, G Napodano… - Radiology, 2024 - pubs.rsna.org
Background Large language models have already demonstrated potential in medical text
processing. GPT-4V, a large vision-language model from OpenAI, has shown potential for …
processing. GPT-4V, a large vision-language model from OpenAI, has shown potential for …
WindowNet: Learnable Windows for Chest X-ray Classification
Public chest X-ray (CXR) data sets are commonly compressed to a lower bit depth to reduce
their size, potentially hiding subtle diagnostic features. In contrast, radiologists apply a …
their size, potentially hiding subtle diagnostic features. In contrast, radiologists apply a …
Establishing the Foundation for Out-of-Distribution Detection in Monument Classification Through Nested Dichotomies
I Antequera-Sánchez, JL Suárez-Díaz… - … Conference on Hybrid …, 2024 - Springer
This paper introduces a hierarchical approach utilizing nested dichotomies to enhance the
MonuMAI framework designed for architectural image classification. The study focuses on …
MonuMAI framework designed for architectural image classification. The study focuses on …