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All Journal Jurnal Riset Kesehatan Jurnal Imejing Diagnostik MATAPPA: Jurnal Pengabdian Kepada Masyarakat Jurnal Radiografer Indonesia Asian Journal of Social and Humanities
Darmini Darmini
Poltekkes Kemenkes Semarang
Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology

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ANALISIS PERBEDAAN KUALITAS CITRA DAN INFORMASI ANATOMI PADA PEMERIKSAAN MRI LUMBAL SEKUEN T2WI FAST SPIN ECHO (FSE) POTONGAN SAGITAL DENGAN VARIASI NILAI TIME REPETITION Merah Bagus YB; Darmini Darmini; Sri Mulyati
JRI (Jurnal Radiografer Indonesia) Vol. 3 No. 1 (2020)
Publisher : Perhimpunan Radiografer Indonesia (PARI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.283 KB) | DOI: 10.55451/jri.v3i1.53

Abstract

Background: Lumbar MRI examination at T2 weighted is recommended using the Fast Spin Echo (FSE) sequence because it can detect early symptoms of a pathology, such as edema, tumors, infections, fractures, ligament injuries, and produce images with strong signals in CSF including details of nerve roots. Based on the observations of researchers at MRCCC Siloam Hospital Semanggi Jakarta that uses TR values ​​in the range of 3500-7500 ms with 3 Tesla MRI. This study aims to determine the differences in image quality and anatomical information as well as knowing the TR values ​​that produce best quality and anatomical information on Lumbar MRI on T2WI FSE. Methods: This type of research is an experiment, then a different friedman test was carried out to determine differences in image quality and anatomical information with variations in TR values ​​that produced best image quality and anatomical information. Result: Friedman test shows there are significant differences between the variation of TR on anatomical information produced with p-value < 0.001. The friedman test results obtained p-value SNR < 0.001, CNR < 0.001 and scan time < 0.001. TR which produces best image quality and anatomical information is TR 5500ms with mean rank 2.32 on Lumbar MRI examination by T2WI FSE sequence sagital slices.
Application of Fusion Technique with ImageJ Stacks Feature for Brain Tumor MRI Image Optimization Nur Wahyu Tajuddin; Bambang Satoto; Rini Indrati; Donny Kristanto Mulyantoro; Darmini Darmini; Gatot Murti Wibowo
Asian Journal of Social and Humanities Vol. 2 No. 11 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i11.359

Abstract

Fusion techniques on MRI for brain tumors can provide comprehensive visualization by combining Axial T2-Flair and Axial T1-GD (T1-weighted post-contrast) sequence images. Fusion MRI in brain tumors is able to clearly display the location, size and characteristics of the tumor. However, not all institutions can install such additional fusion software due to significant additional costs. Therefore, this study aims to prove that the Stacks feature on ImageJ as an alternative can be optimal in visualizing brain tumor image information through MRI fusion techniques. This study used 17 image samples with a quasi experimental design post test only without control group design to compare three analysis methods, namely fusion maximum intensity, minimum intensity and average intensity so that the most suitable projection can be determined. The evaluation of image quality was carried out through a histogram which was then analyzed with a crucal-wallis and the Mann Whitney u test, while the analysis of pathological information used a crucal-wallis, followed by a post hoc test and continued with Mann Whitney u for further analysis. The results show that the stacks feature on ImageJ can be used in the application of fusion techniques so that it will improve the contrast and sharpness of MRI images, especially in areas with high tumor activity. MRI images of brain tumors with maximum fusion intensity produced images with the highest average gray level and the best pathological information. This projection is more optimal than the minimum intensity and average intensity because it provides a more detailed and clear visualization of brain tumors.
Application of Fusion Technique with ImageJ Stacks Feature for Brain Tumor MRI Image Optimization Nur Wahyu Tajuddin; Bambang Satoto; Rini Indrati; Donny Kristanto Mulyantoro; Darmini Darmini; Gatot Murti Wibowo
Asian Journal of Social and Humanities Vol. 2 No. 11 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i11.359

Abstract

Fusion techniques on MRI for brain tumors can provide comprehensive visualization by combining Axial T2-Flair and Axial T1-GD (T1-weighted post-contrast) sequence images. Fusion MRI in brain tumors is able to clearly display the location, size and characteristics of the tumor. However, not all institutions can install such additional fusion software due to significant additional costs. Therefore, this study aims to prove that the Stacks feature on ImageJ as an alternative can be optimal in visualizing brain tumor image information through MRI fusion techniques. This study used 17 image samples with a quasi experimental design post test only without control group design to compare three analysis methods, namely fusion maximum intensity, minimum intensity and average intensity so that the most suitable projection can be determined. The evaluation of image quality was carried out through a histogram which was then analyzed with a crucal-wallis and the Mann Whitney u test, while the analysis of pathological information used a crucal-wallis, followed by a post hoc test and continued with Mann Whitney u for further analysis. The results show that the stacks feature on ImageJ can be used in the application of fusion techniques so that it will improve the contrast and sharpness of MRI images, especially in areas with high tumor activity. MRI images of brain tumors with maximum fusion intensity produced images with the highest average gray level and the best pathological information. This projection is more optimal than the minimum intensity and average intensity because it provides a more detailed and clear visualization of brain tumors.
Co-Authors Agustina Dwi Prastanti Andrey Nino Kurniawan Anggraini Dwi S Arinawati Arinawati Bagus Abimanyu Bambang Satoto Dimas Prakoso Donny Kristanto Mulyantoro Dwi Rochmayanti Eko Kuntjoro Fatimah Fatimah Feni Try Sabdo Gatot Murti Wibowo Himawan Setyono Jannah, Marichatul Khumaidi Khumaidi Merah Bagus YB Muhammad Raizal Rais Nur Wahyu Tajuddin Nurul Fatimah MZ Rasyid Rasyid Rini Indrati Selfia Claudiana Rahma Dewi Siti Daryati Sri Mulyati Yeti Kartikasari