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INDONESIA
Journal of Medical Physics and Biophysics
Published by Himpunan Fisika Medis dan Biofisika Indonesia
ISSN : 23552727     EISSN : 23552719     DOI : -
Core Subject : Health, Science,
Medicine & Pharmacology Physics
Journal of Medical Physics and Biophysics is a gold open-access journal and serves as official publication media of the Indonesian Association of Physicists in Medicine, IAPM (Aliansi Fisikawan Medik Indonesia, AFISMI). JMPB publishes articles with the general concern on the application of physics in medicine and the biological system. The role of physics highlighted in the journal can be of theoretical, experimental, or clinical nature. Review and original articles in radiation oncology, diagnostic and interventional radiology, nuclear medicine, biomaterial, physical biology, physical modeling of biological system, and other related sciences are welcome. Any opinions stated on the articles published in JMPB are those of the author(s) and do not necessarily reflect the policy of IAPM/AFISMI unless otherwise stated.
Arjuna Subject : -
Articles 2 Documents
 1 
Search results for , issue "Vol 9, No 1 (2022)" : 2 Documents clear
Validation of a Newly Installed Secondary Independent Dose Verification System Philip Kioko Ndonye; Samuel Nii Adu Tagoe
Journal of Medical Physics and Biophysics Vol 9, No 1 (2022)
Publisher : Indonesian Association of Physicists in Medicine (AIPM/AFISMI)

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Abstract

Abstract: The aim of the study was to validate a newly installed Mobius 3D (M3D) quality assurance software for use as a secondary independent dose verification system for comparison with an Eclipse treatment planning system (TPS) data of 3D conformal radiotherapy treatment (3D CRT). It is recommended that a secondary MU/dose calculation using a secondary method other than the TPS be performed. A total of 138 treatment fields resulting from 103 patients were planned on the TPS for treatment by 3D CRT. The treatment plans data created on the Eclipse TPS were then exported to the M3D independent verification system and results for both systems were compiled as the output of the M3D system. Percentage 3D Gamma passing rate, mean PTV and OAR dose, the percentage difference between PTV and OAR dose for both systems were generated on the M3D secondary system and the results analyzed. The 3D Gamma passing rates for the 138 patient fields verified had been analyzed graphically and had a mean gamma passing rate of 98.7±0.6 %.  For a treatment plan verification to be acceptable, a minimum gamma passing rate of 95% needs to be achieved. The percentage Gamma passing rates for the patients were well above the minimum acceptable limit of 95% as seen on the graphical results. 3D Gamma passing rates for the 138 patient treatment fields analyzed and verified had a mean passing rate of 98.7±0.6 % which was well above the minimum acceptable limit of 95% and in agreement with published data. The PTV and OAR data for the percentage difference between M3D and TPS were within Action and Tolerance levels determined and thus the M3D system was validated as a secondary independent treatment plans checker for the Eclipse TPS treatment plans at the institution.
Computer-Aided Detection (CAD) Deteksi Nodul Paru-Paru dari Computed Tomography (CT) Osas Lisa Istifarinta; Prawito Prajitno; Djarwani Soeharso Soejoko
Journal of Medical Physics and Biophysics Vol 9, No 1 (2022)
Publisher : Indonesian Association of Physicists in Medicine (AIPM/AFISMI)

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Abstract

Nodul paru merupakan pertumbuhan jaringan abnormal pada paru yang digunakan sebagai diagnosis dini kanker paru. Kanker paru-paru adalah kanker yang paling banyak ditemukan dan mematikan di dunia. Umumnya, deteksi pertama nodul paru diperoleh dari citra CT yang didiagnosis secara visual oleh ahli radiologi. Artinya subjektivitas individu radiologis berpengaruh dalam citra diagnosis tersebut. Untuk membantu ahli radiologi dalam mendeteksi dan mengevaluasi nodul paru pada citra CT secara otomatis, penelitian ini telah mengembangkan sistem Computer-Aided Detection (CAD). Sistem CAD menggunakan metode segmentasi Otsu, dengan ekstraksi fitur Gray Level Co-occurrence Matrix (GLCM) sebagai input untuk klasifikasi nodul. Algoritma Random Forest digunakan untuk membedakan antara normal dan abnormal pada citra CT, khususnya citra dengan kelainan nodul paru. Evaluasi estimasi keberadaan nodul paru pada sistem dilakukan menggunakan Receiver Operating Characteristic (ROC) dengan sensitivitas 95%.Kata Kunci: CAD, CT dada, Deteksi nodul paru, Random Forest

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