Deep learning-based diagnosis of osteoblastic bone metastases and bone islands in computed tomograph images: a multicenter diagnostic study.

ABSTRACT:

Objective

To develop and validate a deep learning (DL) model based on CT for differentiating bone islands and osteoblastic bone metastases.

Materials and methods

The patients with sclerosing bone lesions (SBLs) were retrospectively included in three hospitals. The images from site 1 were randomly assigned to the training (70%) and intrinsic verification (10%) datasets for developing the two-dimensional (2D) DL model (single-slice input) and "2.5-dimensional" (2.5D) DL model (three-slice input) and to the internal validation dataset (20%) for evaluating the performance of both models. The diagnostic performance was evaluated using the internal validation set from site 1 and additional external validation datasets from site 2 and site 3. And statistically analyze the performan

SUBMITTER: Xiong Y 

PROVIDER: S-EPMC10415522 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature