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Chapter and Conference Paper
Mammogram Classification with Ordered Loss
Breast radiologists inspect mammograms with the utmost consideratio...
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Chapter and Conference Paper
Hybrid Mass Detection in Breast MRI Combining Unsupervised Saliency Analysis and Deep Learning
To interpret a breast MRI study, a radiologist has to examine over 1000 images, and integrate spatial and temporal information from multiple sequences. The automated detection and classification of suspicious...
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Chapter and Conference Paper
A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography
This paper addresses the problem of detection and classification of tumors in breast mammograms. We introduce a novel system that integrates several modules including a breast segmentation module and a fibrogl...
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Chapter and Conference Paper
Image De-noising by Bayesian Regression
We present a kernel based approach for image de-noising in the spatial domain. The crux of evaluation for the kernel weights is addressed by a Bayesian regression. This approach introduces an adaptive filter, ...
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Chapter and Conference Paper
Geodesic Active Contours with Combined Shape and Appearance Priors
We present a new object segmentation method that is based on geodesic active contours with combined shape and appearance priors. It is known that using shape priors can significantly improve object segmentation i...