background: accurate brain tissue segmentation from magnetic resonance (mr) images is an important step in analysis of cerebral images. there are software packages which are used for brain segmentation. these packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. thus, assessment of the quality of the segmented gray matter (gm), ...

The goal of forensic dentistry is to identify individuals based on their dental characteristics. This chapter presents a system for automating that process by identifying people from dental X-ray images. Given a dental image of a postmortem (PM), the proposed system retrieves the best matches from an antemortem (AM) database. The system automatically segments dental X-ray images into individual...

Background: Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging.Objective: This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regiona...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

The purpose of this study is to find out if there is a relationship between parameter ofsegmentation and customer satisfaction, in order to find out the current parameter of segmentationin automobile industries In India researcher has gone through several published journal, books,magazines and companies data. The result shows that the most important factor for segmentation ofautomobile industri...

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

This paper presents a novel approach to automatic classifying and identifying of tree leaves using image segmentation fusion. With the development of mobile devices and remote access, automatic plant identification in images taken in natural scenes has received much attention. Image segmentation plays a key role in most plant identification methods, especially in complex background images. Wher...

Non-carious cervical lesions are characterized by the loss of dental hard tissue at the cement-enamel junction (CEJ). Exceeding stresses are therefore generated in the cervical region of the tooth that cause disruption of the bonds between the hydroxyapatite crystals, leading to crack formation and eventual loss of enamel and the underlying dentine. Damage identification was performed by image ...

This paper presents an autonomous framework for building a real 3-D human teeth database. Firstly, teeth fixed over wax are scanned by using a Cone-beam CT scanner. Then, adaptive Level-set segmentation is used to extract teeth from the wax to build the 3-D model. Finally, point-based 3-D shape registration is used to align different teeth models to minimize global differences represented in sc...