Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Elementer (Elektro dan Mesin Terapan)
Yuli Triyani
Universitas Gadjah Mada Politeknik Caltex Riau, Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Computer Aided Diagnosis using Margin and Posterior Acoustic Featuresfor Breast Ultrasound Images Hanung Adi Nugroho; Yuli Triyani; Made Rahmawaty; Igi Ardiyanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.5021

Abstract

Breast cancer is the most commonly diagnosed cancer among females worldwide. Computer aided diagnosis (CAD) was developed to assist radiologists in detecting and evaluating nodules so it can improve diagnostic accuracy, avoid unnecessary biopsies, reduce anxiety and control costs. This research proposes a method of CAD for breast ultrasound images based on margin and posterior acoustic features. It consists of preprocessing, segmentation using active contour without edge (ACWE) and morphological, feature extraction and classification. Texture and geometry analysis was used to determine the characteristics of the posterior acoustic and margin nodules. Support vector machines (SVM) provided better performance than multilayer perceptron (MLP). The performance of proposed method achieved the accuracy of 91.35%, sensitivity of 92.00%, specificity of 89.66%, PPV of 95.83%, NPV of 81.26% and Kappa of 0.7915. These results indicate that the developed CAD has potential to be implemented for diagnosis of breast cancer using ultrasound images.
Perbandingan Teknik Reduksi Derau Speckle Pada Citra Ultrasonograpi Payudara Yuli Triyani; Made Rahmawaty
Jurnal Elektro dan Mesin Terapan Vol. 4 No. 2 (2018): Jurnal Elektro dan Mesin Terapan (ELEMENTER)
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.033 KB) | DOI: 10.35143/elementer.v4i2.2409

Abstract

Breast cancer is the most commonly diagnosed cancer with the highest prevalence, incidence, and mortality rate for females in Indonesia and worldwide. Ultrasonography is a recommended modality for breast cancer, because it is comfortable, radiation free and it can be widely used. However, ultrasound images often occur in quality degradation caused by speckle noise that appears during image acquisition. It causes difficulty for radiologists or Computer Aided Diagnosis (CAD) systems to diagnose these images. Some techniques are proposed for reducing the speckle noise. This journal aims to compare the performance of 14 noise reduction techniques in breast ultrasound images. Quantitative testing was carried out on 58 breast ultrasound images and 3 artificial breast ultrasound image. The quantitative parameters are used include texture analysis (Mean, Variant, skewness, kurtosis, contrast and entropy) and evaluation of image quality (MSE, RMSE, SNR, SSIM, Structural content and Maximum Difference). The qualitative testing was also carried out with the assessment of 3 radiology specialists on 3 samples of each reduction technique. Based on test results, the 3 best performance filters are DsFsrad, DsFamedian dan DsFhmedian. Keywords: Ultrasound, speckle noise, filter
Computer Aided Diagnosis (CAD) untuk Phonocardiogram (PCG) Berbasis Fast Fourier Tranform Yuli Triyani; Wahyuni Khabzli; Noptin Harpawi; Wiwin Styorini
Jurnal Elektro dan Mesin Terapan Vol. 7 No. 1 (2021): Jurnal Elektro dan Mesin Terapan (ELEMENTER)
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (558.084 KB) | DOI: 10.35143/elementer.v7i1.4454

Abstract

Data from WHO 2015 shows that 70% of deaths in the world are caused by non-infection diseases, 45% are caused by heart and blood vessel disease, namely 17.7 million from 39.5 million deaths. Riset Kesehatan Dasar (Riskesdas) reported that in 2018, there were 15 of 1000 people, or 2,784,064 individuals in Indonesia suffering from heart disease. Symptoms of heart abnormalities often come suddenly. Therefore, early recognition can help to avoid heart attacks. Doctors currently use a heart sound / phonocardiogram (PCG) to assess the performance of the heart using a stethoscope. The PCG’s diagnosis is very influenced by the subjectivity of doctors because of its relatively weak and physical limitations. So that the possibility of a False Positive Result happening is quite high. To minimize this risk, a Computer Aided Diagnosis (CAD) PCG signal was developed. Several studies have proposed a PCG diagnostic method using the wavelet or Welch method and based on Neural Network are more complex. In this study, a simple diagnosis method is proposed so that the computation is easier and faster with good accuracy. The PCG signal is amplified twice, then the Fast Fourier Transform (FFT) process is carried out to obtain the characteristics of the fundamental frequency and max amplitude. The classification stage uses the Multi Layer Perceptron (MLP). From testing of 55 data PCG, the results obtained accuracy of 90%, sensitivity of 80%, PPV of 100% and NPV of 83.33%. Keywords: PCG, CAD, FFT, frekuensi fundamental, classification
Co-Authors Elfrida Ratnawati Igi Ardiyanto Made Rahmawaty, Made Noptin Harpawi Wahyuni Khabzli Wiwin Styorini