Transformative Advances in AI for Precise Cancer Detection: A Comprehensive Review of Non-Invasive Techniques

Archives of Computational Methods in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 11, 2025

Language: Английский

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Automatic Active Contour Algorithm for Detecting Early Brain Tumors in Comparison with AI Detection

Processes, Journal Year: 2025, Volume and Issue: 13(3), P. 867 - 867

Published: March 15, 2025

The automatic detection of objects in medical photographs is an essential component the diagnostic procedure. issue early-stage brain tumor has progressed significantly with use deep learning algorithms (DLA), particularly convolutional neural networks (CNN). lies fact that these necessitate a training phase involving large database over several hundred images, which can be time-consuming and require complex computational infrastructure. This study aimed to comprehensively evaluate proposed method, relies on active contour algorithm, for identifying distinguishing tumors magnetic resonance images. We tested algorithm using 50 specifically focusing glioma tumors, while 2000 images were used DLA from BRATS Challenges 2021. segmentation method made up anisotropic diffusion filter pre-processing, (Chan-Vese), morphologic operations refinement. evaluated its performance various metrics, such as accuracy, precision, sensitivity, specificity, Jaccard index, Dice Hausdorff distance. provided average first six metrics 0.96, higher than most classical image methods was comparable methods, have score 0.98. These results indicate ability detect accurately rapidly. section both numerical visual insights into similarity between segmented ground truth areas. findings this highlighted potential computer-based improving identification imaging. Future work must validate efficacy approaches across different categories improve computing efficiency integrate technology clinical processes.

Language: Английский

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Innovative deep learning and quantum entropy techniques for brain tumor MRI image edge detection and classification model

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 122, P. 588 - 604

Published: March 20, 2025

Language: Английский

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Efficient Approach for Brain Tumor Detection and Classification Using Fuzzy Thresholding and Deep Learning Algorithms

IEEE Access, Journal Year: 2025, Volume and Issue: 13, P. 78808 - 78832

Published: Jan. 1, 2025

Language: Английский

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