13 citations · 33 across the 5 of their papers we have counts for
19 papers
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation
Qinji Yu, Kang Dang, Nima Tajbakhsh +2
Despite the tremendous success of deep neural networks in medical image segmentation, they typically require a large amount of costly, expert-level annotated data. Few-shot segment…
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang +1
Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from co…
End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery
Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
The automated segmentation of buildings in remote sensing imagery is a challenging task that requires the accurate delineation of multiple building instances over typically large i…
Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images
Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5
Scoliosis is a congenital disease that causes lateral curvature in the spine. Its assessment relies on the identification and localization of vertebrae in spinal X-ray images, conv…
Progressive Adversarial Semantic Segmentation
Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
Medical image computing has advanced rapidly with the advent of deep learning techniques such as convolutional neural networks. Deep convolutional neural networks can perform excee…
Edge-Gated CNNs for Volumetric Semantic Segmentation of Medical Images
Ali Hatamizadeh, Demetri Terzopoulos, Andriy Myronenko
Textures and edges contribute different information to image recognition. Edges and boundaries encode shape information, while textures manifest the appearance of regions. Despite…