The project aims at developing a tool to be used by the radiologists for detection of Brain Tumors in MRI images automatically.

Every year thousands of people die around the globe as a result of different brain tumors. Some due to human incapability because of large variations in size, location and form of the Brain Tumors, while some due to human errors because of increasing number of Neuro-patients leading to a huge manual workload on small Radiology group.

This inspired us to develop a tool which can assist radiologist by automatically detecting Brain Tumors in MRI images and thus help in Saving Time, Saving Money and Saving Radiologist for more complex and expertise requiring cases

Current Situation


To come up with next generation MRI viewers which can assist the radiologists by automatically detecting Tumor, if present and generate report based on the tumor found.

Input : Like a normal Dicom Viewer, it loads ‘n’ patient cases with 20 slices(MRI images) each of T2, T1,T1 post contrast,etc sequences.

Output : Divide the loaded ‘n’ number of cases into three categories and generate report for each patient case automatically.

The three categories are


We have been working on this Idea from summer’11 as part of SURA (Summer Undergraduate Reasearch Award) and have developed a Prototype for testing the above made algorithm. Testing dataset so far, consist of 120 patients (each patient data consists of 20 images each of 3 sequences T1, T2 and T1 post contrast) and is gradually expanded. Out of 120, 65 were Normal and 55 abnormal (30 Tumor containing).

The AutoCom prototype showed excellent results differentiating normal-abnormal as well as identifying Tumor and generating report, when found.