Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach

Results in Control and Optimization, Год журнала: 2025, Номер unknown, С. 100533 - 100533

Опубликована: Фев. 1, 2025

Язык: Английский

A Content-Based Medical Image Retrieval System for Lung Diseases Using Mask AttnRCNNpro Segmentation and Hybrid Distance Approach

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 14, 2025

At present, Content-Based Medical Image Retrieval Systems (CBMIRS) are a novel and potentially useful technology though they lack clinical validation. The study aims to assess how CBMIRS helps in interpretation of chest X-ray (CXR) images patients who have lung disease. This paper proposes Lung-CBMIR, new hybrid model that enhance retrieval precision computational complexity for disease images. system combines Mask AttnR-CNNpro, an improved segmentation uses attention mechanisms precisely segment areas. Feature extraction is done through Local Binary Patterns (LBP) texture features, shape descriptors geometric pattern, DenseNet+, which utilizes three dense blocks strategic pooling methods achieve deep feature extraction. Bobcat-Fish Hybrid Optimizer (BFHO) method proposed this integrates Bobcat Optimization exploration ability with the exploitation capability Catch Fish optimal selection features. There also distance metric, combining Mahalanobis Cosine distances, improves image similarity measurement. Furthermore, rank based on their relevance query compile them into vector. Lastly, DeepCL-Net classifier, combination Convolutional Neural Networks (CNN) Long Short-Term Memory (LSTM) networks, facilitates effective classification illnesses like pneumonia, infiltrates, nodules. Lung-CBMIR found attain accuracy 98.75%, F1-score 98.13%, MCC 0.9801, better than state-of-the-art models CNN-AE 95.58% VGG-19 96.81%. results confirm greatly accuracy, lowers complexity, yields strong tool diagnosis CBMIR tasks. abbreviation concern description manifested Table 1.

Язык: Английский

Enhanced multiple sclerosis diagnosis by MRI image retrieval using convolutional autoencoders

Egyptian Informatics Journal, Год журнала: 2025, Номер 30, С. 100698 - 100698

Опубликована: Май 24, 2025

Язык: Английский