Diabetic retinopathy image classification with quantitative saliency-oriented visual explanation and SLIC-G image preprocessing methods - Lim, Wei Xiang (2024)
The field of medical image analysis has seen remarkable progress, primarily propelled by advancements in Convolutional Neural Networks (CNNs). These sophisticated neural networks have demonstrated their value across various applications, including the detection of lung cancer and segmentation of brain tumors. Such instances highlight CNNs’ potential to significantly enhance the accuracy of medical image analysis, suggesting their role in improving clinical outcomes. Despite these advancements, the inherently opaque nature of CNNs often categorizes them as ”black boxes”, raising concerns about their transparency.