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Found 4 papers, 1 papers with code
Analysis of Macula on Color Fundus Images Using Heightmap Reconstruction Through Deep Learning
For medical diagnosis based on retinal images, a clear understanding of 3D structure is often required but due to the 2D nature of images captured, we cannot infer that information.
Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks
For screening, 3D shape of the eye retina often provides structural information and can assist ophthalmologists to diagnose diseases.
Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph
With the increasing usage of radiograph images as a most common medical imaging system for diagnosis, treatment planning, and clinical studies, it is increasingly becoming a vital factor to use machine learning-based systems to provide reliable information for surgical pre-planning.
Estimation of Pelvic Sagittal Inclination from Anteroposterior Radiograph Using Convolutional Neural Networks: Proof-of-Concept Study
Alignment of the bones in standing position provides useful information in surgical planning.
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