6 citations · 6 across the 2 of their papers we have counts for
3 papers
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts
Gaurav Fotedar, Nima Tajbakhsh, Shilpa Ananth +1
Supervised learning has proved effective for medical image analysis. However, it can utilize only the small labeled portion of data; it fails to leverage the large amounts of unlab…
ErrorNet: Learning error representations from limited data to improve vascular segmentation
Nima Tajbakhsh, Brian Lai, Shilpa Ananth +1
Deep convolutional neural networks have proved effective in segmenting lesions and anatomies in various medical imaging modalities. However, in the presence of small sample size an…
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth +3
Reliable and automatic segmentation of lung lobes is important for diagnosis, assessment, and quantification of pulmonary diseases. The existing techniques are prohibitively slow,…