A Novel Classification and Diagnosis of Multiple Sclerosis Method using Artificial Neural Networks and Improved Multi-Level Adaptive Conditional Random Fields

Seyedeh R. Mahmudi Nezhad Dezfouli; Y. Kyani; Seyed A. Mahmoudinejad Dezfouli

Articles in Press, Accepted Manuscript, Available Online from 27 February 2022

http://dx.doi.org/10.22044/jadm.2021.10647.2201

Abstract
  Due to the small size, low contrast, variable position, shape, and texture of multiple sclerosis lesions, one of the challenges of medical image processing is the automatic diagnosis and segmentation of multiple sclerosis lesions in Magnetic resonance images. Early diagnosis of these lesions in the first ...  Read More

H.5.7. Segmentation
Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing

V. Naghashi; Sh. Lotfi

Volume 7, Issue 4 , November 2019, , Pages 507-519

http://dx.doi.org/10.22044/jadm.2019.3935.1464

Abstract
  Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering ...  Read More

H.3.2.2. Computer vision
A Pixon-based Image Segmentation Method Considering Textural Characteristics of Image

M. H. Khosravi

Volume 7, Issue 1 , January 2019, , Pages 27-34

http://dx.doi.org/10.22044/jadm.2017.5988.1706

Abstract
  Image segmentation is an essential and critical process in image processing and pattern recognition. In this paper we proposed a textured-based method to segment an input image into regions. In our method an entropy-based textured map of image is extracted, followed by an histogram equalization step ...  Read More

H.5. Image Processing and Computer Vision
Modified CLPSO-based fuzzy classification System: Color Image Segmentation

A.M. Shafiee; A. M. Latif

Volume 2, Issue 2 , July 2014, , Pages 167-179

http://dx.doi.org/10.22044/jadm.2014.356

Abstract
  Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting ...  Read More