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...

Image co-segmentation is an active computer vision task that aims to segment the common objects from a set of images. Recently, researchers design various learning-based algorithms undertake task. The main difficulty in this how effectively transfer information between images make conditional predictions. In paper, we present CycleSegNet, novel framework for Our network has two key components: ...

WinBank is a system which performs automated reading of handwritten documents, particularly of strings of handwritten numerals on bank checks. A commonly-used strategy for reading handwritten strings is a combination of segmentation and recognition. In the WinBank program, segmentation involves both the separation of touching characters and the merging of character fragments to other pieces. An...

we first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. the band-dependent posterior probability that the hard segmentation columnv...

Segmentation of lung anatomical parts like fissures and bronchopulmonary segments are of clinical importance in interpreting and assessing the pathologies present in the lungs. Segmentation of fissures still remains a challenging task as the selection of the segmentation algorithm decides the accuracy of the fissure segmentation. We conducted experiments on the existing segmentation methods and...

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...