We propose a novel deformable model with statistical and deterministic components for LV segmentation in cardiac magnetic resonance (MR) cine images. The statistical deformable component learns a global reference model of the LV using Principal Component Analysis (PCA) while the deterministic deformable component consists of a finite-element deformable surface superimposed on the reference mode...

Kidney function evaluation using dynamic contrast-enhanced MRI (DCE-MRI) images could help in diagnosis and treatment of kidney diseases of children. Automatic segmentation of renal parenchyma is an important step in this process. In this paper, we propose a time and memory efficient fully automated segmentation method which achieves high segmentation accuracy with running time in the order of ...

Cardiac resynchronization therapy is a treatment option for patients suffering from symptomatic heart failure. The problem with this treatment option is, that 30% to 40% of the patients do not respond. One reason might be the inappropriate placement of the left ventricular lead via the coronary sinus. Therefore, endocardial pacing systems have been developed. Nonetheless, the implantation of th...

Plagiarism is defined as an unauthorized act of using or adapting others’ works and ideas without referring to them. Numerous methods have been proposed to detect plagiarism in different languages; however, not a lot has been accomplished in Persian. The present study has utilized statistical and semantic features to determine the functionality of Support Vector Machines (SVMs) in detecting act...

Background/Aim: This study aimed to determine appropriate deformable image registration (DIR) algorithms for pancreatic cancer patients undergoing carbon ion radiotherapy (CIRT). Patients and Methods: The performance of three types DIR algorithms, including intensity-based (iDIR), contour-based (cDIR), hybrid (hDIR) were evaluated using seventy-one CT images from eight patients. Both the geomet...

Segmentation of medical images has been the most demanding and growing area currently for analysis images. polyp is a huge challenge because variability color depth morphology in polyps throughout colonoscopy imaging. For segmentation, this work, we have used dataset gastrointestinal polyp. The algorithms paper segmentation depend on profound deep convolutional neural network architectures: FCN...

This paper is devoted to propose cosine, Dice and Jaccard similarity measures of interval rough neutrosophic set and interval neutrosophic mean operator. Some of the properties of the proposed similarity measures have been established. We have proposed multi attribute decision making approaches based on proposed simlarity measures. To demonstrate the applicability and efficiency of the proposed...

This paper discusses ways in which the similarity between the contents of two referring expressions can be measured. Similarity metrics of this kind are essential when expressions generated by an algoritm are compared against the ones produced by human speakers, for example as part of an experiment in which referring expressions are elicitated. We discuss arguments for and against different met...

Spleen volume estimation using automated image segmentation technique may be used to detect splenomegaly (abnormally enlarged spleen) on Magnetic Resonance Imaging (MRI) scans. In recent years, Deep Convolutional Neural Networks (DCNN) segmentation methods have demonstrated advantages for abdominal organ segmentation. However, variations in both size and shape of the spleen on MRI images may re...