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21 results for “Magnetic Resonance (MR) Images”
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Research ArticleOpen accessEvery word in the titleHeart Localization from Magnetic Resonance Images SequenceAhmed Farag, Mahmoud FakhreldinProblem statement: Heart localization is an important step in cardiac Magnetic Resonance Images (MRI) analysis. This study aims to locate the moving heart region from MRI sequence of images. Approach: The idea is to use the motion detection techniques to isolate the heart region from the background image and then apply morphological operations to construct a moving heart region mask. … …Journal of Computer Science, Vol. 8, Issue 4 · 30 Jan 2012 · 6,852 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBrain Tumor Segmentation and Classification Using HardNet Transformer With Gated Recurrent Unit ModelSaida D, Srinivas Adepu, Thade Lakshmi Devi et al.The uncontrolled growth of brain tumor cells presents a severe health risk, making early diagnosis and accurate classification essential for improving treatment outcomes. However, the existing approaches used for segmentation fail to delineate the tumor regions accurately due to a lack of global contextual information of brain tumors, resulting in poor classification performance. To overcome this limitation, this research proposes … …Journal of Computer Science, Vol. 22, Issue 9 · 26 Sep 2026 · 630 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEnhancing Brain MR Image Quality Using CNN With Best Denoising Modality for Improved Diagnosis of Abnormality: An AppraisalKavery Verma, Subodh Srivastava, Ritesh Kumar MishraDigital medical images acquired from the brain are highly susceptible to noise, which causes significant challenges for radiologists to identify abnormalities in a precise manner. Noise interference hampers both diagnostic accuracy and the interpretation of underlying abnormalities, potentially leading to flaw conclusions. Magnetic Resonance (MR) imaging is the most preferred digital imaging technique for brain abnormality detection. To achieve precise … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,462 accessesView PDFCite
Research ArticleOpen accessIn the abstractMRI Observation and Analysis of Muscle Activity During ExerciseLi-Chang Zou, Hong-Wu LiWhile conventional biomechanical testing techniques are able to determine the mechanical characteristics of muscle tissue, they do not offer precise insight into how muscle metabolism and microstructure change in response to various types of exercise activities over the course of time. Using Magnetic Resonance Imaging (MRI) analysis of muscle tissue allows researchers to examine how different levels of intensity affect … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 30 Jul 2026 · 1,025 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Networks and Contrast-Limited Adaptive Histogram Equalization Filter Based Early-Stage Breast Cancer Detection TechniquesAnitha Ponraj, Aroul CanessaneBreast cancer is one of the most common types of cancer that kills women. When cells become uncontrollably large, cancer develops. As a result, detecting and classifying breast cancer in its early stages is essential so that patients can take the appropriate precautions. On the other hand, mammography images have relatively low sensitivity and effectiveness in detecting breast cancer. Furthermore, … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,613 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Disease Prediction through Ensembled Transfer Learning on Cardiac Magnetic Resonance ImagingSibu Cyriac, Sivakumar R., Nidhin RajuCardiovascular Diseases (CVD) cause more deaths worldwide than most of the other diseases. The diagnosis of cardiovascular disease from Magnetic Resonance Imaging plays a major role in the medical field. The technological revolution contributed a lot to increase the effectiveness of CVD diagnosis. Many Artificial Intelligence methods using Deep Learning models are available to assist the cardiologist in the diagnosis … …Journal of Computer Science, Vol. 18, Issue 11 · 2 Nov 2022 · 6,169 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel SIFT-SVM Approach for Prostate Cancer DetectionSwetha Parvatha Reddy Chandrasekhara, Mohan Govindsa Kabadi, SrivinayProstate cancer is a major cause of concern in male population as it is said to affect 1 in every 7 men in their lifetime. The number of cases being registered for prostate cancer and its mortality rates are increasing yearly at an alarming rate. Due to the high resolution and multi-dimensionality of the Magnetic Resonance Imaging (MRI) images, proper … …Journal of Computer Science, Vol. 16, Issue 12 · 22 Dec 2020 · 7,524 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,074 accessesView PDFCite