168 citations · 243 across the 5 of their papers we have counts for
5 papers
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network
Raunak Dey, Wenbo Sun, Haibo Xu +1
In this paper we consider the problem of unsupervised anomaly segmentation in medical images, which has attracted increasing attention in recent years due to the expensive pixel-le…
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
Raunak Dey, Yi Hong
We introduce a neural network framework, utilizing adversarial learning to partition an image into two cuts, with one cut falling into a reference distribution provided by the user…
Hybrid Cascaded Neural Network for Liver Lesion Segmentation
Raunak Dey, Yi Hong
Automatic liver lesion segmentation is a challenging task while having a significant impact on assisting medical professionals in the designing of effective treatment and planning…
CompNet: Complementary Segmentation Network for Brain MRI Extraction
Raunak Dey, Yi Hong
Brain extraction is a fundamental step for most brain imaging studies. In this paper, we investigate the problem of skull stripping and propose complementary segmentation networks…
Diagnostic Classification Of Lung Nodules Using 3D Neural Networks
Raunak Dey, Zhongjie Lu, Yi Hong
Lung cancer is the leading cause of cancer-related death worldwide. Early diagnosis of pulmonary nodules in Computed Tomography (CT) chest scans provides an opportunity for designi…