Deep learning based automatic detection, and localization of cancer region using multispectral photoacoustic imaging

Photoacoustic imaging (PAI) has the potential to detect cancer in the early stage. PAI is safe due to its non-ionizing radiation properties, which greatly enhance its clinical feasibility in the near future, which provides significant benefits over other imaging techniques like X-ray computed tomography (CT). In this paper, the fully automated 3D deep learning cancer detector is taken to detect and localize the presence of cancer in freshly excised ex-vivo human thyroid and prostate tissue specimens using a three-dimensional (3D) multispectral photoacoustic (MPA) dataset automatically. The model detected and localized the cancer region in a given test MPA image with promising results.