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74 articles for “MRI”
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Research ArticleOpen accessIn the abstractA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,861 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 · 1,484 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,435 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 · 5,617 accessesView PDFCite
Review ArticleOpen accessIn the abstractReview on Different Algorithms and Techniques Used in Classification of Gender in SilkwormJyoti Sharma, Pradeep ChoukseySilkworm seed is the key factor for the success of sericulture industry. Silk seed production process at grain ages centre mainly involve procuration of seed cocoon, cutting of seed cocoon for pupae, separation of male and female pupae, emergence of moth, coupling of silk moth and further egg laying by female moth. Separation of male and female is very much … …Journal of Computer Science, Vol. 21, Issue 6 · 17 Jun 2025 · 4,040 accessesView PDFCite
Case ReportOpen accessIn the abstractBrief Report: 20-Year Follow-Up of an Infant with Neurological Impairment Born to a Mother with Variant Creutzfeldt-Jakob DiseaseJustin Penner, Anjali Rampersad, James E. Burns et al.A term infant born via uncomplicated caesarian section was noted to be jittery, hypotonic, and have pooling of secretions at birth. Over the first four weeks of life, the infant developed four limb hypertonia, hyperreflexia, and clonus. MRI at 3.5 weeks old showed brain immaturity, poor myelination, and increased signal in the dorsal thalami. At six months, dystonic features with … …American Journal of Infectious Diseases, Vol. 21, Issue 1 · 7 Mar 2025 · 7,666 accessesView PDFCite
Research ArticleOpen accessIn the abstractExperimental Evaluation of Adaptive Step-Size Based FxLMS Approach for Active Noise Control in Magnetic Resonance Imaging SystemsI. Juvanna, Uppu Ramachandraiah, G. Muthukumaran et al.Magnetic Resonance Imaging (MRI) scanners emit up to 135 decibels of acoustic noise, which is a major source of discomfort for patients and personnel evaluating them during routine medical scans, necessitating the development of a method to reduce the acoustic noise generated during MRI testing. The goal of this study is to propose a frequency-domain Active Noise Control (ANC) method … …Journal of Computer Science, Vol. 18, Issue 12 · 24 Nov 2022 · 5,511 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 · 6,171 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Classification Model using CNN for Detection of Alzheimer’s DiseaseRagavamsi Davuluri, Ragupathy RengaswamyAlzheimer’s Disease (AD) is commonly called a neurodegenerative disorder and it is a common form of dementia. There is no permanent cure for this brain disease hence the early diagnosis of such disease using medical imaging system is highly significant. Machine learning models play a vital role in the detection of AD. Since most of the conventional machine learning models … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 6,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosing Alzheimer’s Disease using Convolution Neural NetworksSarita, Saurabh Mukherjee, Tanupriya Choudhury et al.Alzheimer’s is a disease wherein constant degeneration of neurons and their synapses result in impaired brain functioning which leads to personality changes, memory loss, thinking and speech disorder. So, there is a requirement of an automated and early diagnosis of this disease to decrease the death rate. The proposed work is coupled with deep learning techniques to predict the Alzheimer’s … …Journal of Computer Science, Vol. 18, Issue 2 · 21 Feb 2022 · 7,350 accessesView PDFCite