Claim Missing Document
Check
Articles

Found 3 Documents
Search

BENEFITS OF STEEPING BLACK TEA AS A NEGATIVE CONTRAST MEDIUM ON CT UROGRAPHY EXAMINATION Sagita Yudha; Suharyo Hadisaputro Hadisaputro; Jeffri Ardiyanto; Donny Kristanto Mulyantoro; Siti Masrochah
Journal of Applied Health Management and Technology Vol 2, No 2 (2020): April 2020
Publisher : Politeknik Kesehatan Kementerian Kesehatan Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (823.425 KB) | DOI: 10.31983/jahmt.v2i2.5697

Abstract

The use of water as a contrast medium requires large amounts of water to fill the lumen of the Urinary Tractus and more water is reabsorbed by the body than is secreted into urine. Steeping Black tea contains Caffeine which is able to increase blood flow in the kidneys thus inhibiting the process of absorption of Na, Ca and Mg causing stimulation of the kidneys to increase the amount of urine production. The purpose of this study is to prove that drinking black tea can increase urine production as a negative contrast medium to see differences in the distension and density of the Urinary Tract on CT Urography examination. This type of research uses True Experimental with Pretest-Posttest Control Group Design research design. Patients selected by Simple Random Sampling. Analysis: Paired t test and Independent t test. The results of the study of the use of 600 ml steeping Black Tea as a negative contrast medium on CT Urography examination did not show the difference in mean difference between the left renal Pelvis p value 0.956, Left UVJ 0.640, Right UVJ 0.935 while on the right renal Pelvis p value 0.001 showed differences in mean difference between the left renal Pelvis p value 0.956, Left UVJ 0.640, Right UVJ 0.935 while on the right renal Pelvis p value 0.001 intervention and control group. Hasil pengukuran p value  densitas Vesika urinaria sebesar 0,678. Conclusion: Black tea can be used as a negative contrast medium on CT Urographic examination but when compared with mineral water it does not show a significant difference.
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.