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All Journal Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Applied Health Management and Technology Jurnal Ners Science Midwifery International Journal of Health Science and Technology
Hidayat, Fathur Rachman
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Humanities Computer Science & IT Control & Systems Engineering Dentistry Electrical & Electronics Engineering Engineering Health Professions Medicine & Pharmacology Nursing Public Health Veterinary

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Journal : Science Midwifery

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Analysis of axial T2 TSE images using deep learning reconstruction in MRI of brain tumors Muzdalifah, Nadifah Pratiwi; Utami, Hernastiti Sedya; Hidayat, Fathur Rachman; Wibowo, Kusnanto Mukti; Jadmika, Muhammad Riefki; Samudra, Alan
Science Midwifery Vol 13 No 1 (2025): April: Health Sciences and related fields
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/midwifery.v13i1.1867

Abstract

Magnetic Resonance Imaging (MRI) Brain examinations often encounter uncooperative patients, necessitating rapid scanning techniques that yield optimal results. To address this challenge, advanced technologies such as deep learning can be leveraged to accelerate scan time, reduce noise, and enhance image precision. This study aims to evaluate the disparity in MRI Brain image quality with and without deep learning in tumor cases to achieve superior diagnostic imaging. Employing a quantitative experimental approach, this research analyzed a sample of 30 patients collected from January to February 2025. Three Radiologist Specialists assessed the images using a questionnaire based on the Visual Grading Analysis (VGA) method. The obtained responses were statistically examined through Cohen’s Kappa consistency test and Wilcoxon Signed-Rank Test. Findings revealed a statistically significant difference in image information between deep learning-assisted and conventional MRI scans. In T2 TSE sequences, deep learning reconstruction demonstrated superior anatomical visualization of the Gray Matter, White Matter, Lateral Ventricles, Basal Ganglia, and Parafalx Cerebri. However, in brain tumor pathology visualization, conventional MRI exhibited sharper and more distinct tumor delineation. Although deep learning-enhanced T2 TSE sequences reduced scan duration and improved overall image quality, they provided suboptimal diagnostic information in tumor cases.
Analysis of differences in anatomical information in magnetic resonance cholangiopancreatography (MRCP) examinations between the use of the mouth breath hold technique and trigger technique Rahmawan, Sahrul; Fitriana, Lutfatul; Hidayat, Fathur Rachman; Samudra, Alan
Science Midwifery Vol 13 No 2 (2025): June: Health Sciences and related fields
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/midwifery.v13i2.1915

Abstract

MRCP is a non-invasive imaging method used to visualize the biliary system and detect abnormalities in the bile ducts or gall bladder. In taking images, there are two techniques, namely the mouth breath hold (MBH) technique and the trigger technique, where the MBH technique is carried out by the radiographer giving instructions directly related to the patient's respiratory movements, while the trigger technique uses respiratory gating to detect breathing patterns and minimize image blur due to organ movement. At Department of Radiology SMC Telogorejo Semarang both techniques are used in MRCP examinations by looking at the condition of each patient. So the author is interested in comparing the results of anatomical information from the two techniques. Methods: This research uses a quantitative design with an experimental approach. Data was collected from 10 patients who underwent MRCP examinations at the Department of Radiology SMC Telogorejo Semarang in August–September 2024. The scanning procedure was carried out using a T2 HASTE coronal section sequence twice for each patient using the MBH and trigger technique. Anatomical information was assessed by means of visual grading analysis by 3 radiologists on the structure of the cystic duct, intra-hepatic duct, common hepatic duct, common bile duct, pancreatic duct, and gallbladder (gallbladder) using a questionnaire with a scale (1–4). Then the data was analyzed using SPSS to determine whether there were differences in image information from the two techniques using the Wilcoxon difference test. This research has passed the ethical test number: KEPK/UMP/170/I2025. Results: Based on the results of the Wilcoxon test, both for the entire anatomy and for each anatomy, it shows a p-value < 0.05. This indicates that there are significant differences in the anatomical information produced by the two techniques. Based on the mean rank value, the most optimal technique for displaying anatomical information is MBH. This advantage is due to its ability to reduce movement artifacts through the breath-hold method, resulting in clearer and more detailed anatomical images compared to the trigger technique. The MBH technique is more effective in improving MRCP anatomical information, especially in patients with respiratory instability. It is hoped that these results can be a reference in determining the optimal method for MRCP examination.
Co-Authors Ariesma Githa Giovany Faesol, Ahmad Fitriana, Lutfatul Jadmika, Muhammad Riefki Masghuri, Hakim Muzdalifah, Nadifah Pratiwi Permana, Hendry Dwi Widya Pranandya, Brian Ilham Rahardian, Arga Pratama Rahmawan, Sahrul Safitri, Ara Novita Samudra, Alan Susanto, Fani Utami, Hernastiti Sedya W, Kusnanto Mukti Wahyu Caesarendra Wati, Kristina