340 citations · 506 across the 9 of their papers we have counts for
9 papers
Machine learning applications using diffusion tensor imaging of human brain: A PubMed literature review
Ashirbani Saha, Pantea Fadaiefard, Jessica E. Rabski +2
We performed a PubMed search to find 148 papers published between January 2010 and December 2019 related to human brain, Diffusion Tensor Imaging (DTI), and Machine Learning (ML).…
Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model
Mateusz Buda, Ashirbani Saha, Ruth Walsh +5
Breast cancer screening is one of the most common radiological tasks with over 39 million exams performed each year. While breast cancer screening has been one of the most studied…
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
Mateusz Buda, Ashirbani Saha, Maciej A Mazurowski
Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associated with shape features. In this study, we propose a fully automatic way to quant…
Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images
Jun Zhang, Ashirbani Saha, Brian J. Soher +1
Objective: To develop an automatic image normalization algorithm for intensity correction of images from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acqui…
Deep learning in radiology: an overview of the concepts and a survey of the state of the art
Maciej A. Mazurowski, Mateusz Buda, Ashirbani Saha +1
Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve complex problems. Deep l…
Deep Learning for identifying radiogenomic associations in breast cancer
Zhe Zhu, Ehab Albadawy, Ashirbani Saha +3
Purpose: To determine whether deep learning models can distinguish between breast cancer molecular subtypes based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).…
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ
Zhe Zhu, Michael Harowicz, Jun Zhang +4
Purpose: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the di- agnosis of ductal ca…
High Frequency Content based Stimulus for Perceptual Sharpness Assessment in Natural Images
Ashirbani Saha, Q. M. Jonathan Wu
A blind approach to evaluate the perceptual sharpness present in a natural image is proposed. Though the literature demonstrates a set of variegated visual cues to detect or evalua…
Full-reference image quality assessment by combining global and local distortion measures
Ashirbani Saha, Q. M. Jonathan Wu
Full-reference image quality assessment (FR-IQA) techniques compare a reference and a distorted/test image and predict the perceptual quality of the test image in terms of a scalar…