Ricci Curvature Based Volumetric Segmentation of the Auditory Ossicles

by   Na Lei, et al.

The auditory ossicles that are located in the middle ear are the smallest bones in the human body. Their damage will result in hearing loss. It is therefore important to be able to automatically diagnose ossicles' diseases based on Computed Tomography (CT) 3D imaging. However CT images usually include the whole head area, which is much larger than the bones of interest, thus the localization of the ossicles, followed by segmentation, both play a significant role in automatic diagnosis. The commonly employed local segmentation methods require manually selected initial points, which is a highly time consuming process. We therefore propose a completely automatic method to locate the ossicles which requires neither templates, nor manual labels. It relies solely on the connective properties of the auditory ossicles themselves, and their relationship with the surrounding tissue fluid. For the segmentation task, we define a novel energy function and obtain the shape of the ossicles from the 3D CT image by minimizing this new energy. Compared to the state-of-the-art methods which usually use the gradient operator and some normalization terms, we propose to add a Ricci curvature term to the commonly employed energy function. We compare our proposed method with the state-of-the-art methods and show that the performance of discrete Forman-Ricci curvature is superior to the others.


page 7

page 10

page 11

page 12

page 16

page 18

page 19

page 20


A lateral semicircular canal segmentation based geometric calibration for human temporal bone CT Image

Computed Tomography (CT) of the temporal bone has become an important me...

Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation

Lymphoma detection and segmentation from whole-body Positron Emission To...

Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes

Quantification of adipose tissue (fat) from computed tomography (CT) sca...

Dual Shape Guided Segmentation Network for Organs-at-Risk in Head and Neck CT Images

The accurate segmentation of organs-at-risk (OARs) in head and neck CT i...

A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images

Radiation therapy (RT) is widely employed in the clinic for the treatmen...

AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

The aortic vessel tree is composed of the aorta and its branching arteri...

Fluid segmentation in Neutrosophic domain

Optical coherence tomography (OCT) as retina imaging technology is curre...

Please sign up or login with your details

Forgot password? Click here to reset