About Us

BrIC lab focuses on developing neuroinformatics techniques using machine learning, statistical modeling, and pattern recognition for applications in brain tumors and neurological disorders. One of the primary focuses of BrIC lab is to identify computerized image-based (also known as radiomic) phenotypes, and their associations with genomics (radiogenomics) and histo-pathology (radio-pathomics) for disease characterization.

Our vision is to conduct interdisciplinary and translational research in personalized diagnostics towards early diagnosis, prognosis, and response to treatment for  different neurological conditions including brain tumors. Through our clinical collaborations and research efforts, we aim to build technologies with a potential for near-term clinical impact in customizing personalized treatments and improving patient survival.

Our lab is located at Case Western Reserve University,  within School of Medicine and Case Comprehensive Cancer Center, and is affiliated with the Center for Computational Imaging and Personalized Diagnostics


Please check the research page for specific projects and research focus of our group.

February 11, 2020

BrIC lab paper awarded the "Most Cited Paper Award 2017"

BrIC lab paper entitled "Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings", was published in European Radiology in 2017, and has received 57 citations in the two years following publication (2018-2019). It was, therefore, awarded a "Most Cited Paper Award 2017" for receiving the second highest number of citations.

December 20, 2019

BrIC lab awarded the prestigious V Foundation Award

BrIC lab in collaboration with Cleveland Clinic was awarded a 3-year V Foundation Translational Award for their work on capturing tumor heterogeneity on post-treatment MRIs

December 20, 2019

Niha Beig to serve term as Trainee Editorial Board member for journal Radiology: Artificial Intelligence

Niha has been selected for a one-year term as a Trainee Editorial Board member for the journal Radiology: Artificial Intelligence. Niha will learn the intricacies of scientific journalism, contribute to content on the applications of artificial intelligence in radiology and help continue to build the future of the journal. 

October 15, 2019

Three BrIC lab papers have been accepted at SPIE

BrIC lab's paper on identifying gender-specific differences in ASD versus controls using deep learning features combined with hand-crafted features, has been accpeted for publication at SPIE 2020.

Ashish's paper has also been accepted, entitled "Quality assessment of MRI using a dense neural network model".

Ramon's paper entitled "lesson-habitat' radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumor," has also been accepted for publication.

October 13, 2019

Dr. Tiwari gave 3 keynote talks at MICCAI 2019 workshops

Dr. Tiwari gave keynotes talks at 3 workshops at MICCAI this year. On 13th October, she talked at AI in neuro-oncology workshop. On the 17th, she presented BrIC lab's work at the Medical Image Learning with Less Labels and Imperfect Data Workshop and BrainLes workshop

August 15, 2019

BrIC lab's RSNA abstract has been accepted

Work on Radiogenomic Analysis of Glioblastoma on Pre-treatment Gd-T1w MRI Reveals Gender-specific Imaging Features and Signaling Pathways, has been accepted at RSNA 2019.

July 26, 2019

Dr. Tiwari participated in inaugural Young Investigators Forum in Neuro-Oncology.

Dr. Tiwari participated as one of 40 young investigators in the inaugural 2019 Young Investigators Forum in Neuro-Oncology held in Atlanta.

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