Skeletal muscle is an adaptive tissue with the ability to regenerate in response to exercise
training. Cross-sectional area (CSA) quantification, as a main parameter to assess muscle …

Understanding the changes in choroidal thickness and vasculature is important to monitor
the development and progression of various ophthalmic diseases. Accurate segmentation of …

Choroid is one of the structural layers, playing a significant role in physiology of the eye and
lying between the sclera and the retina. The segmentation of this layer could guide …

Content-based image retrieval (CBIR) has become one of the most important research
directions in the domain of digital data management. In this paper, a new feature extraction …

Convolutional neural networks are sensitive to unknown noisy condition in the test phase
and so their performance degrades for the noisy data classification task including noisy …

In this work, a new clustering algorithm is proposed based on neutrosophic set (NS) theory.
The main contribution is to use NS to handle boundary and outlier points as challenging …

Purpose: To develop an open-source, fully automatic deep learning algorithm, DeepGPET,
for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We …

Purpose: To develop Choroidalyzer, an open-source, end-to-end pipeline for segmenting
the choroid region, vessels, and fovea, and deriving choroidal thickness, area, and vascular …

Retinal diseases can be manifested in optical coherence tomography (OCT) images since
many signs of retina abnormalities are visible in OCT. Fluid regions can reveal the signs of …

The performance of convolutional neural networks is degraded by noisy data, especially in
the test phase. To address this challenge, a new convolutional neural network structure with …