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Innovative Multimodal Approaches in Image-Based Analysis of Adipose Tissue Cells Syah Putra, Heru; Mukhtar, Husneni; Alia, Fenty; Adipurna Syamsunarno, Mas Rizky Anggun
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i4.30241

Abstract

This study addresses the limitations of traditional single-modality imaging techniques, such as optical microscopy, in effectively analyzing adipose tissue cells. A novel multimodal approach is introduced to overcome these challenges, combining MRI, CT, and microscopy to provide a more comprehensive and precise dataset. The system automates image processing, utilizing advanced segmentation methods to detect adipose cells more accurately while calculating cell dimensions and total image area. The results indicate that the maximum observed cell diameter reaches 10,466.64 µm, with a minimum diameter of 0.40 µm and an average diameter of 2,398.31 µm across the sample images. All measurements achieved 0% mean square error (MSE), highlighting the precision of the method. Comparative analysis reveals significant improvements in accuracy for both cell detection and quantification, outperforming conventional methods. Graphical representations further validate the reliability of this multimodal approach, demonstrating its capacity to capture intricate details of cellular structures. This innovative method holds considerable promise for enhancing medical diagnostics, particularly in metabolic disorders like obesity and diabetes, where adipose tissue plays a pivotal role. Integrating multiple imaging modalities offers a powerful tool for more informed clinical decisions, potentially leading to improved patient outcomes.
The Initial Development of Integrated Add-On Tele-Ultrasonography for Monitoring the Health of Pregnant Women and Fetuses in the Community Health Centers in Indonesia: - Susanti, Hesty; Setiyadi, Suto; Puspitasari, Dita; Alia, Fenty; Ramadhan, Muhammad Rizqi Syah
Journal of Engineering and Technological Sciences Vol. 57 No. 6 (2025): Vol. 57 No. 6 (2025): December
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2025.57.6.9

Abstract

Maternal health and fetal growth in rural areas require special attention due to limited access to adequate healthcare systems. Early detection of fetal health conditions can be achieved using B-mode ultrasonography (USG). However, expectant mothers in these regions often lack regular to regular check-up, even when healthcare facilities are available there may not be trained professionals available to analyze the B-mode images obtained in the Community Health Centres. To address this gap, a tele-USG system was developed that allows healthcare workers in remote areas to operate basic USG equipment and transmit real-time images to specialist doctors at higher-level healthcare facilities. During system development, a general-purpose USG phantom was used to test parameters: penetration depth, geometric accuracy, focal zone, and axial and lateral resolution. Testing confirmed that both USG and laptop used for streaming produce reliable and accurate results. A slight geometric representation differences of 2.74% (approximately 1 cm per target) was observed, attributed to dimensional distortion between devices with different monitor sizes. In geometric accuracy tests, five out of eight vertical and six out of seven horizontal targets were successfully detected. The smallest variation of 0.028 mm occurred at 5 MHz frequency, demonstrated high precision focal zone measurements. The axial resolution ranged between 0.25-0.5 mm, while lateral resolution ranged from 1.0-2.0 mm, indicating strong capability for fine-detail imaging. Overall, the system exhibited high sensitivity and excellent imaging performance, offering a promising solution to enhance maternal and fetal healthcare challenges faced by rural communities in Indonesia through accessible real-time diagnostic support