Yogi Ramadhani
Jenderal Soedirman University

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Computer Aided Diagnosis for Screening the Shape and Size of Leukocyte Cell Nucleus based on Morphological Image Retno Supriyanti; Alfin Chrisanty; Yogi Ramadhani; Wahyu Siswandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.699 KB) | DOI: 10.11591/ijece.v8i1.pp150-158

Abstract

Hematology tests are examinations that aim to know the state of blood and its components, one of which is leukocytes. Hematologic examinations such as the number and morphology of blood generally still done manually, especially by a specialist pathologist. Despite the fact that today there is equipment that can identify morphological automatically, but for developing countries like Indonesia, it can only be done in the capital city. Low accuracy due to the differences identified either by doctors or laboratory staff, makes a great reason to use computer assistance, especially with the rapid technological developments at this time. In this paper, we will emphasize our experiment to screen leucocyte cell nucleus by identifying the contours of the cell nucleus, diameter, circumference and area of these cells based on digital image processing techniques, especially using the morphological image. The results obtained are promising for further development in the development of computer-aided diagnosis for identification of leukocytes based on a simple and inexpensive equipment.
Preliminary process in blast cell morphology identification based on image segmentation methods Retno Supriyanti; Pangestu F. Wibowo; Fibra R. Firmanda; Yogi Ramadhani; Wahyu Siswandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1269.138 KB) | DOI: 10.11591/ijece.v10i6.pp5714-5725

Abstract

The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required in CBC examinations. However, the CBC process still poses a problem, namely that the procedure for manually counting blood cells with a microscope requires a lot of energy and time, and is expensive. This paper will discuss alternative uses of image processing technology in blast cell identification by using microscope images. In this paper, we will discuss in detail the morphological measurements which include the diameter, circumference and area of blast cell cells based on watershed segmentation methods and active contour. As a basis for further development, we compare the performance between the uses of both methods. The results show that the active contour method has an error percentage of 5.15% while the watershed method has an error percentage of 8.25%.
Point Processing Method for Improving Dental Radiology Image Quality Retno Supriyanti; Ariep Soelaiman Setiadi; Yogi Ramadhani; Haris Budi Widodo
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.3 KB) | DOI: 10.11591/ijece.v6i4.pp1587-1594

Abstract

Radiology field is very important in today's world, especially in the field of medicine including dentistry. Radiology equipment that is popular in dentistry is the panoramic machine. A panoramic image facilitate the dentist in making a diagnosis of the abnormality in the mouth and teeth. But unfortunately, for developing countries like Indonesia, panoramic machine available are low resolution which have an effect on the resulting image also has low quality. This research aims to improve the quality of the panoramic image to have a better quality. We use point processing method with emphasis on contrast stretching method. We chose this method because it is quite simple but has a high performance. Based on the second opinion from the hospital, the performance is 83.9%, therefore this method is promising to be implemented on the improvement of dental radiology images.
Simple Screening for High-Risk Pregnancies in Rural Areas Based on an Expert System Retno Supriyanti; Ahmad Fariz; Teddy Septiana; Eko Murdyantoro; Yogi Ramadhani; Haris Budi Widodo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.988

Abstract

The high maternal and infant mortality rates in developing countries, especially Indonesia, are quite alarming. There are many factors that cause high mortality numbers; one of them is the delay in handling cases of high‑risk pregnancies. The main problem faced by developing countries is the lack of health facilities, including medical equipment and human resources. This research aims to develop a simple system that can be used to screen high‑risk pregnancies. This system is based on an expert system. The Analytical Hierarchy Process (AHP) method is used in making decisions about potentially high-risk pregnancy patients. Essentially, the system can be used by anyone, anywhere, to carry out early screening of high‑risk pregnancy patients, so that delays in the treatment of these patients can be resolved, because the symptoms of high‑risk pregnancy are known from the beginning. Results indicate that this system shows promise for further development. 
Coronal slice segmentation using a watershed method for early identification of people with Alzheimer's Retno Supriyanti; Anugerah Kevin Marchel; Yogi Ramadhani; Haris Budi Widodo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15142

Abstract

One physical sign of a person who has Alzheimer's is the diminution of the area of the hippocampus and ventricles. A good quality magnetic resonance imaging (MRI) will provide a high-quality image so that the doctor will quickly analyze the abnormalities of the hippocampus and ventricle area. However, for low-quality MRI, this is difficult to do. This condition will be a significant problem for some regions in developing countries including Indonesia, where many hospitals have only low-quality MRI, and many hospitals do not have them at all. The primary purpose of this research is to develop simple tools to analyze morphological characteristics in Alzheimer's patients. In this paper, we focus only on coronal slice analysis. We will use watershed method segmentation, because of this method able to segment the boundaries automatically, so that parts of the hippocampus and ventricles can be identified in an MRI image. Analysis of morphological characteristics is also classified by age and gender. Then by referring to the value of the clinical dementia rating (CDR), the process of identifying between images with Alzheimer's disease (AD) and healthy models is done based on the morphological analysis that has been done. The results show this method has a better performance compared to the previously work.
Separability Filter for Localizing Abnormal Pupil: Identification of Input Image Retno Supriyanti; Elvin Pranata; Yogi Ramadhani; Tutik Ida Rosanti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 4: December 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i4.1200

Abstract

 Separability filter method is a reliable method for pupil detection. However, so far this method is implemented for detecting pupil of normal eye, while for abnormal eye such as cataract and glaucoma patients; they have different characteristics of pupil such as color, shape and radius size of pupil. In this paper we propose to use separability filter for detecting pupil of abnormal patients with different characteristics. We faced a problem about radius size, shape and color of pupil; therefore we implemented Hough Transform, Blob area and Brightness for identifying input images before applying separability filter. The experiment results show that we can increase performance of pupil detection for abnormal eye to be 95.65%.
Brightness and Contrast Modification in Ultrasonography Images Using Edge Detection Results Retno Supriyanti; Suwitno Suwitno; Yogi Ramadhani; Haris Budi Widodo; Tutik Ida Rosanti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3440

Abstract

Currently, ultrasonography device become an important equipment for supporting diagnosis in diesases. Unfortunetaly, a lot of ultrasonography images do not provide enough information for supporting diagnosis especially images produced by low-resolution ultrasonography. It is caused by image quality that has been produced is inadequate because of noise. This research aims to improve image quality by modifying brightness and contrast to the edge detection algorithms. By modifying the brightness and contrast will cause the value of standard deviation of the ultrasonography image is lowered. Raising setting values will cause deviation standard value becomes smaller, and also the result of standard deviation is inversely proportional to the value of RMSE.  The results show that this modification can improve image quality by reducing noise significantly.
Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation Retno Supriyanti; Muhammad Alqaaf; Yogi Ramadhani; Haris B. Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1074-1083

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has made test screening much needed. Currently, the most commonly used is the swab type. Although in fact, there is also a screening method with chest radiology. The purpose of this study is to develop a COVID-19 early detection system based on X-ray images of the patient's thorax in the form of a computer-aided diagnosis. This case is based on the fact that X-ray modalities are available in several health care centers in Indonesia, compared to other modalities such as computed tomography (CT) scan or magnetic resonance imaging (MRI). In this paper, we emphasize the X-ray thorax image segmentation process to explore the morphological information of the thorax. We use the Bradley thresholding segmentation method. The results obtained are promising to be further developed with a performance percentage of 73.33% for the thorax for COVID-19 patients and 54% for the thorax for normal patients.
Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method Retno Supriyanti; Muhammad Rifqi Kurniawan; Yogi Ramadhani; Haris Budi Widodo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp315-324

Abstract

COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication of how badly COVID-19 is attacking the patient. We use X-Ray Thorax image objects as research data in this paper. Although the current experimental results show that this method has a successful performance of 71.11%, it is pretty promising for further development due to its simplicity.
Morphological features of lung white spots based on the Otsu and Phansalkar thresholding method Retno Supriyanti; Syadzwina Luke Dzihniza; Muhammad Alqaaf; Muhammad Rifqi Kurniawan; Yogi Ramadhani; Haris Budi Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp530-539

Abstract

COVID-19 is a disease that causes respiratory system disorders, so various tests are needed. One of them uses a chest X-ray or thorax. A chest X-ray will depict the lungs as a whole so that patches like white shadows will be visible. In this study, the number of lung areas and white spots can be observed and detected using segmentation techniques in image processing. But before entering the segmentation stage, the image will go through the preprocessing stage using the tri-threshold fuzzy intensification operators (fuzzy IO) method. It then segmented the lungs using the Otsu method by changing the digital image from grey to black and white based on comparing the threshold value with the pixel colour value of the digital image. Then, further segmentation was carried out using the Phansalkar method to detect and simultaneously count the number of white spots. Referring to the experiments we have carried out, Otsu Phansalkar's segmentation performance promises to be developed further.