Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

ABSTRACT:

Purpose

Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often requiring further investigations. Deep learning (DL) - a machine learning technique designed to mimic human neuronal interactions- has shown promise in the field of medical imaging analysis for different purposes, including segmentation and classification of lesions. In this study, we aim to develop a DL algorithm that can classify areas of increased uptake on bone scintigraphy scans.

Methods

We collected 2365 BS from three European medical centres. The model was trained and validated on 1203 and 164 BS scans respectively. Further

SUBMITTER: Ibrahim A 

PROVIDER: S-EPMC9875407 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature