What exactly is a Bio-imaging bank, and how does it help in detecting cancer?

The Tata Memorial Hospital of Mumbai welcomed the artificial intelligence technology to detect cancer in their patients. 

The biggest cancer hospital in the country set up a Bio-Imaging Bank through which it makes use of deep learning for the task of creating a cancer-specific algorithm. This algorithm in turn helps in early-stage cancer detection. 

The Bio Imaging Bank works on deep learning for which it processed data from over 60,000 patients last year. 

Here we explain what exactly is a Bio Imaging Bank. 

What exactly is a Bio-Imaging Bank? 

The mission of the project is to build a strong repository that comprises a myriad of images related to pathology and radiology. It also consists of clinical data, treatment specifics, outcome information, and extra metadata. 

Next, this huge bank of information is designed in a way that it can train and test AI algorithms.

At the starting stage, the project stresses lung cancers and head-neck cancers. It is focusing on at least 1000 patients for each of these cancer types.
While initially this number is set, the project aspires to surpass the number by the end.
One of the tasks of the project is to train and test a variety of AI algorithms with the help of the data collected, catering to important medical tasks like nucleus segmentation, screening for lymph node metastases, therapy response prediction, and more. 

The Department of Biotechnology, in collaboration with RGCIRC- New Delhi, PGIMER- Chandigarh, IIT-Bombay, and AIIMS-New Delhi, has funded the project.

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Cancer detection through artificial intelligence 

Artificial intelligence is adding a lot to the lives of people in almost all fields, and now, the medical field is no exception, as the technology helps detect cancer. The artificial intelligence technology emulates the information processing of the human brain. It analyses pathological and radiological pictures, learns from datasets, recognizes distinct features linked to cancers, and thus detects cancers in patients. The technology comes to extreme benefit as it identifies tissue changes, thereby fostering the chances of early detection.

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