Putra, Heru Syah and Mukhtar, Husneni and Alia, Fenty and Syamsunarno, Mas Rizky A.A (2024) Innovative Multimodal Approaches in Image-Based Analysis of Adipose Tissue Cells. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), 10 (4). pp. 723-733.
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5-Innovative Multimodal Approaches in Image-Based Analysis of Adipose Tissue Cells (Repaired).pdf Download (1MB) |
Abstract
Adipose tissue analysis using traditional techniques, such as optical microscopy, faces limitations in narrow field of view, low resolution, and manual analysis prone to operator bias. These challenges become more relevant in research related to obesity and metabolic disorders, where the accuracy of white adipose tissue (WAT) quantification is critical. The research contributions are to develop a multimodal imaging approach integrating MRI, CT, and optical microscopy for more comprehensive white adipose tissue analysis and apply automated algorithms to improve the efficiency and accuracy of adipose tissue segmentation and quantification. This approach utilizes the advantages of each modality: MRI for soft tissue analysis, CT for three-dimensional detail, and optical microscopy for cellular-level resolution. An automated system was designed to process images, detect cells, calculate cell dimensions, and analyze the total area of adipose tissue in sample images. The results showed a maximum cell diameter of 10,466.64 µm, a minimum diameter of 0.40 µm, and an average diameter of 2,398.31 µm with 0% mean square error (MSE), reflecting high precision in measurement. Comparative analysis revealed that this method is significantly more accurate than traditional techniques. Graphical representation validates the reliability of this approach for detecting intricate details of cellular structures. This multimodal approach offers innovative solutions to the challenges of adipose tissue analysis, providing reliable diagnostic tools for the management of obesity and metabolic disorders. Integration of these imaging modalities can improve informed clinical decisions, potentially resulting in better patient outcomes and accelerating metabolic research.
Item Type: | Artikel Umum |
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro) |
Depositing User: | M.Eng. Alfian Ma'arif |
Date Deposited: | 05 Feb 2025 02:53 |
Last Modified: | 05 Feb 2025 02:53 |
URI: | http://eprints.uad.ac.id/id/eprint/79646 |
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