A review on automated algorithms used for osteoporosis diagnosis
G Amiya, K Ramaraj, PR Murugan… - Inventive Systems and …, 2022 - Springer
Osteoporosis is a major public health issue requiring significant resources to address the
immediate and long-term consequences of fractures. Only a few research studies have been …
immediate and long-term consequences of fractures. Only a few research studies have been …
Minimally parametrized segmentation framework with dual metaheuristic optimisation algorithms and FCM for detection of anomalies in MR brain images
S Natarajan, V Govindaraj, Y Zhang… - … Signal Processing and …, 2022 - Elsevier
Background Early prognosis of a brain tumour may offer better life expectancy. Magnetic
Resonance Imaging (MRI) coupled with an efficient machine learning segmentation …
Resonance Imaging (MRI) coupled with an efficient machine learning segmentation …
Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling
Abstract Background and Objective: This paper proposes a fully automated and
unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs …
unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs …
A novel triple-level combinational framework for brain anomaly segmentation to augment clinical diagnosis
S Natarajan, V Govindaraj… - Computer Methods in …, 2022 - Taylor & Francis
Medical image segmentation techniques have become a very imperative prerequisite for
accuracy and easiness of diagnosis in image analysis processes. An effective and novel …
accuracy and easiness of diagnosis in image analysis processes. An effective and novel …
A smartly designed automated map based clustering algorithm for the enhanced diagnosis of pathologies in brain MR images
V Senthilvel, V Govindaraj, YD Zhang… - Expert …, 2021 - Wiley Online Library
The competitive segmentation of fuzzy clustering is utilized in a greater manner to deal with
the local spatial information of input medical images. Fuzzy clustering favours lesions and …
the local spatial information of input medical images. Fuzzy clustering favours lesions and …
Distance Metric-based Segmentation and Score-Level Classification for Optimized Tumor Identification in MR Images
D Jithendra Reddy, T Arun Prasath… - IETE Journal of …, 2023 - Taylor & Francis
Tumors in the brain and pancreas are formed by abnormal cells accumulating in a tissue
mass in the human body. The standard technique for MRI tumor detection and …
mass in the human body. The standard technique for MRI tumor detection and …
[PDF][PDF] Examining the Pathological Portions in MR Brain Slices using Automated Map and Improved Fuzzy K-Means Clustering
Identification of pathological structures (tissue and tumor region) in brain MR images is
executed by an automated algorithm, and it requires improvement in processing time and …
executed by an automated algorithm, and it requires improvement in processing time and …
[PDF][PDF] An Automated Map Process Based Improved Fuzzy C-Means Algorithm for Pathological Detection in MR Image
Automated brain MR slices segmentation process is difficult, and further difficult is the
process of detecting the tumor and tissue regions, with a constraint of delivering higher …
process of detecting the tumor and tissue regions, with a constraint of delivering higher …
[引用][C] Efficient automatic segmentation of multi-domain imagery using ensemble feature-segmenter pairs with machine learning
P Pachunde - Turkish Journal of Computer and Mathematics …, 2021