This AI toolkit uses deep learning algorithms for its segmentation of tumors into four tissue categories consisting of non-tumoral, enhancing proliferative, peritumoral edema, and necrotic.

nnU-Net: A Self-Configuring Method for Deep Learning-Based Biomedical Image Segmentation. Nature Methods , 2020 DOI: 10.1038/s41592-020-01008-z Cite This Page : ...

When it comes to diagnosing brain cancer, biopsies are often the first port of call. Surgeons begin by removing a thin layer of tissue from the tumour and examining it under a microscope, looking ...

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study. The Lancet Digital Health , 2022; 4 (9): e657 DOI: 10.1016/S2589 ...

Please use one of the following formats to cite this article in your essay, paper or report: APA. Cuffari, Benedette. (2025, April 07). Using Deep Learning for Brain Imaging Data Analysis.

It uses deep learning, a form of artificial intelligence, to recognize patterns in large volumes of data. In this case, the data is the amino acid sequences of proteins called T cell receptors (TCRs).