3.3k citations · 3.3k across the 2 of their papers we have counts for
5 papers
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou +2
Medical images are naturally associated with rich semantics about the human anatomy, reflected in an abundance of recurring anatomical patterns, offering unique potential to foster…
Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE)
Germán González, Daniel Jimenez-Carretero, Sara Rodríguez-López +17
Rationale: Computer aided detection (CAD) algorithms for Pulmonary Embolism (PE) algorithms have been shown to increase radiologists' sensitivity with a small increase in specifici…
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh +4
Generative adversarial networks (GANs) have ushered in a revolution in image-to-image translation. The development and proliferation of GANs raises an interesting question: can we…
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee +4
Transfer learning from natural image to medical image has established as one of the most practical paradigms in deep learning for medical image analysis. However, to fit this parad…
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu +4
Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure pro…