Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : indonesian journal of applied physics

Lung Cancer Detection Using a Modified Convolutional Neural Network (CNN) Cari Cari; Mohtar Yunianto; Aisyah Ajibah Rahmah
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 14, No 1 (2024): April
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v14i1.77032

Abstract

Image processing is used to classify lung images with malignant or normal nodules. The Convolutional Neural Network (CNN) method is often used to classify images. This study uses a modified CNN architecture with various layers, filters, batch size, dropout, and epoch values. Variations were made to determine the best accuracy value and reduce the overfitting value of the proposed CNN architecture. This study implements the method using the Keras library with the Python programming language. The data is in the form of CT-Scan images of lung cancer and normal lungs. The results of several experiments from the proposed model produce an accuracy value of 95% using three layers, 128 filters on the first layer, 256 on the second layer, and 512 filters on the third layer, then with 32 batch sizes, 0.5 dropout.
Performance Analysis of EPC Material as a Kidney Organ Phantom with Exposure Voltage Variations and PA-GF-Based Kidney Stone Size Cari Cari; Mohtar Yunianto; Fuad Anwar; Hardo Ardiansyah Gilang Permadi
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 15, No 2 (2025): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v15i2.106579

Abstract

Research in the field of radiodiagnostics has been extensively developed, creating the need for substitute objects to represent human organs—namely, radiological phantoms. A phantom is a simulated model of an organ fabricated using 3D printing technology. This study aims to evaluate the suitability of Expanded Polyamide – Glass Fiber (EPA-GF) as a kidney stone phantom material embedded within a kidney phantom, based on parameters such as material density, CT number, electron density, and radiation dose across various CT scan exposure voltages. The phantom samples were printed using a dual-extruder 3D printer, with Expanded Polycarbonate (EPC) used as the kidney phantom material. CT scan exposure voltages were set to 80 kV, 100 kV, and 120 kV. Kidney stone sizes used in this study ranged from 1 mm to 8 mm (1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, and 8 mm). The measured density of EPA-GF was 1.51 ± 0.06 g/cm³. The CT numbers obtained at each voltage were 373.30 HU, 329.05 HU, and 299.46 HU, respectively. The corresponding electron density values were 1.231, 1.210, and 1.196, respectively. The effective doses measured at each voltage were 0.0240 mSv, 0.0448 mSv, and 0.0798 mSv. All parameter values were found to be closely aligned with literature references. The smallest visible kidney stone size detected was 2 mm.