Heart and bladder detection and segmentation on FDG PET/CT by deep learning.

ABSTRACT:

Purpose

Positron emission tomography (PET)/ computed tomography (CT) has been extensively used to quantify metabolically active tumors in various oncology indications. However, FDG-PET/CT often encounters false positives in tumor detection due to ¹⁸fluorodeoxyglucose (FDG) accumulation from the heart and bladder that often exhibit similar FDG uptake as tumors. Thus, it is necessary to eliminate this source of physiological noise. Major challenges for this task include: (1) large inter-patient variability in the appearance for the heart and bladder. (2) The size and shape of bladder or heart may appear different on PET and CT. (3) Tumors can be very close or connected to the heart or bladder.

Approach

A deep learning based approach is proposed to segment the heart

SUBMITTER: Wang X 

PROVIDER: S-EPMC8977865 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature