Moch Arief Soeleman

Submitted: 04 January 2026 You are already at the latest version Diabetic retinopathy (DR) is a leading cause of vision impairment and permanent blindness worldwide, requiring an accurate and automated system to classify its multi-grade severity to ensure timely patient intervention. However, standard Convolutional Neural Networks (CNNs) often struggle to capture the fine, high-frequency microvascular patterns critical for diagnosis.

You are already at the latest version Medical image segmentation, especially in chest X-ray (CXR) analysis, encounters substantial problems such as class imbalance, annotation inconsistencies, and the necessity for accurate pathological region identification. This research introduces NCT-CXR, a robust framework that enhances semantic segmentation in CXR images using an improved coordinate-geometric transformation strategy.