Jufriadif Na'am
Universitas Putra Indonesia YPTK Padang

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

Filter technique of medical image on multiple morphological gradient (MMG) method Jufriadif Na'am; Johan Harlan; Rosda Syelly; Agung Ramadhanu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.9722

Abstract

Filter technique is supportive for reducing image noise. This paper presents a study on filtering medical images, i.e., CT-Scan, Chest X-ray and Panoramic X-ray collected from two of the most prominent public hospitals in Padang City, Indonesia. The aim of this study preserved to facilitate in diagnosing objects in x-ray medical images. This study used filter technique, i.e. Blur, Emboss, Gaussian, Laplacian, Roberts, Sharpen, or Sobel techniques as pre-processing step. The filter process performed before edge detection and edge clarification. MMG method used in this study to clarify the edge detection. Thus, this research showed the hesitation decline (confidence increase) of the diagnosis of objects contained in medical images.
An Automatic ROI of The Fundus Photography Jufriadif Na'am; Johan Harlan; Irawadi Putra; Romi Hardianto; Mutiana Pratiwi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.832 KB) | DOI: 10.11591/ijece.v8i6.pp4545-4553

Abstract

The Region of interest (ROI) of the fundus photography is an important task in medical image processing. It contains a lot of information related to the diagnosis of the retinal disease. So the determination of this ROI is a very influential first step in fundus image processing later. This research proposed a threshold method of segmentation to determine ROI of the fundus photography automatically. Data to be elaborated were the fundus photography’s of 13 patients, captured using Nonmyd7 camera of Kowa Company Ltd in Dr. M. Djamil Hospital, Padang. The results of this processing could determine ROI automatically. The automatic cropping successfully omits as much as possible the non-medical areas shown as darkbackground, while still maintaining the whole medical areas, comprised the posterior pole of retina captured through the pupil. Thus, this method is  helpful in further image processing of posterior areas. We hope that this research will be useful for researchers.
Detection of Proximal Caries at The Molar Teeth Using Edge Enhancement Algorithm Jufriadif Na'am; Johan Harlan; Sarifuddin Madenda; Julius Santony; Catur Suharinto
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.732 KB) | DOI: 10.11591/ijece.v8i5.pp3259-3266

Abstract

Panoramic X-Ray produces produces the most common oral digital radiographic image that it used in dentistry practice. The image can further improve accuracy compared to analog one. This study aims to establish proximal caries edge on enhancement images so they can be easily recognized. The images were obtained from the Department of Radiology, General Hospital of M. Djamil Padang Indonesia. Total file of images to be tested were 101. Firstly, the images are analyzed by dentists who practiced at Segment Padang Hospital Indonesia. They concluded that there is proximal caries in 30 molar teeth. Furthermore, the images were processed using Matlab software with the following steps, i.e. cropping, enhancement, edge detection, and edge enhancement. The accuracy rate of detection of edge enhancement images being compared with that of dentist analysis was 73.3%. In the edge enhancement images proximal caries edge can be found conclusively in 22 teeth and dubiously in eight teeth. The results of this study convinced that edge enhancement images can be recommended to assist dentists in detecting proximal caries. 
Enlarge Medical Image using Line-Column Interpolation (LCI) Method Jufriadif Na'am; Julius Santony; Yuhandri Yuhandri; Sumijan Sumijan; Gunadi Widi Nurcahyo
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.955 KB) | DOI: 10.11591/ijece.v8i5.pp3620-3626

Abstract

Quality of medical image has an important role in constructing right medical diagnosis. This paper recommends a method to improve the quality of medical images by increasing the size of the image pixels. By increasing the size of pixels, the size of the objects contained therein is also greater, making it easier to observe. In this study medical images of Brain CT-Scan, Chest X-Ray and Panoramic X-Ray were processed using Line-Column Interpolation (LCI) Method. The results of the treatment are then compared to Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) processing results. The experiment shows that Line-Column Interpolation Method produces a larger image with details of the objects in it are not blurred and has equal visual effects. Thus, this method is expected to be a reference material in enlarging the size of the medical image for ease in clinical analysis.
Image Processing of Panoramic Dental X-Ray for Identifying Proximal Caries Jufriadif Na'am; Johan Harlan; Sarifuddin Madenda; Eri Prasetyo Wibowo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6856

Abstract

This study aims to facilitate the identification of proximal caries in the Panoramic Dental X-Ray  image. Twenty-seven X-Ray images of proximal caries were elaborated. The images in digital form were processed using Matlab and Multiple Morphological Gradient. The process produced sharper images and clarifies the edges of the objects in the images. This makes the characteristics of the proximal caries and the caries severity can be identified precisely.