A method framework of semi-automatic knee bone segmentation and reconstruction from computed tomography (CT) images.

ABSTRACT:

Background

Accurate delineation of knee bone boundaries is crucial for computer-aided diagnosis (CAD) and effective treatment planning in knee diseases. Current methods often struggle with precise segmentation due to the knee joint's complexity, which includes intricate bone structures and overlapping soft tissues. These challenges are further complicated by variations in patient anatomy and image quality, highlighting the need for improved techniques. This paper presents a novel semi-automatic segmentation method for extracting knee bones from sequential computed tomography (CT) images.

Methods

Our approach integrates the fuzzy C-means (FCM) algorithm with an adaptive region-based active contour model (ACM). Initially, the FCM algorithm assigns membership degrees to each vo

SUBMITTER: Humayun A 

PROVIDER: S-EPMC11485355 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature