Maneerat, Noppadol
Loading...
13 results
Now showing 1 - 10 of 13
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automatic exudate extraction for early detection of Diabetic Retinopathy(2013-01-01); ; Diabetic Retinopathy (DR) is the most common cause of blindness in diabetic patients, but early detection and timely treatment can prevent this problem. Exudates have been found to be one of the signs and serious DR anomalies so the proper detection of these lesions and the treatment should be done immediately to prevent loss of vision. The aim of this study is to automatically detect these lesions in fundus images. To achieve this goal, the proposed method first preprocesses to improve the quality of fundus image, and then Optic Disc (OD) is detected and eliminated to prevent the interference to the result of exudate detection by combination of 3 methods; image binarization, Region Of Interest (ROI) based segmentation and Morphological Reconstruction (MR). Next, exudates are detected by applying the maximum entropy thresholding to filter out the bright pixels from the result of OD region eliminated. Since the result contains some noises which appear as bright light at the edge of fundus area in some images, that affect is considered and eliminated to improve the result of false positive. Finally, exudates are extracted by using MR. The proposed technique has been tested on 100 fundus images from hospital. Experimental results show that 91 % of exudate is extracted correctly with the average process of 3.92 second per image. © 2013 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Routing algorithms with adaptive weight function based on total wavelengths and expected available wavelengths in optical WDM networks(2005-01-01); ; Varakulsiripunth, RuttikornThis paper studies routing and wavelength assignment in wavelength-routed (WR) optical WDM networks which are circuit-switched in nature. When a session request is given, (be hard task of routing and wavelength assignment (RWA) is to calculate the satisfiable path between two nodes, and also to assign an available set of wavelengths along this path. Therefore, we have proposed a new routing and wavelength assignment algorithm, called Total wavelengths and Expected available wavelengths (TEW) algorithm in order to achieve the effective routing and wavelength assignment that can guarantee the service for user's requirement. The link weight function is considered as the main factor for route selection in TEW algorithm. This function is calculated by using a determination factor of the number of wavelengths that are being used currently and are supposed to be available after a certain time. The session requests from users will be routed on the links that has the least number of link weights by using Dijkstra's shortest path algorithm. This means that the selected lightpath will have the minimum utilization and maximum expected available wavelengths. The impact of proposed link weight computing function on the blocking probability is investigated by means of computer simulation and comparing with the traditional mechanism. The results show that the proposed TEW algorithm can achieve better performance in terms of the blocking probability. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Brain Tumor Classification using Supervised Support Vector Machine(2023-01-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of protégé, SWRL and SQWRL in fuzzy ontology-based menu recommendation(2009-12-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Provision of Thai herbal recommendation based on an ontology(2010-08-23); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Composition of service and protocol specifications in asynchronous communication system(2004-01-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An ontology-based multi agent autotnotive parts transportation management system(2013-12-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automatic microaneurysms detection through retinal color image analysis(2013-01-01); ; ; Panjaphongse, RonakornThis paper proposes an automatic system to diagnose the diabetic retinopathy symptom, which can cause a loss of vision by analysis the abnormality in retinal image. Digital image processing system is developed for the retinal image analysis which helps ophthalmologists to identify diabetic patients. The retinal images derived from ophthalmologists are used to analysis by using HSV, area identification and eccentricity techniques to distinguish diabetic retinopathy symptoms from normal diabetic patients. First color bar is evaluated by using HSV method and then using the eccentricity technique with area of pixel to find out the abnormality of Microaneurysms (MAs). The accuracy result of experiment is around 93% when compares to the analysis of ophthalmologists. © 2013 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Feature extraction from retinal fundus image for early detection of diabetic retinopathy(2013-12-01); ; Varakulsiripunth, RuttikornAutomated detection of lesions in retinal fundus image can be aid in the detection of diabetic retinopathy. Exudates are the early sign of diabetic retinopathy so the proper detection of these lesions is an essential task in an automatic retinal screening. On the research work leading to automatic analysis of exudate detection, the knowledge of Optic Disk (OD) location is very useful. An efficient algorithm is presented to detect the OD and exudate which are the most important features for early detection of diabetic retinopathy. From a retinal fundus image, the proposed method first preprocesses and estimates the histogram of retinal background, then filters out the bright pixels in intensity image. They include OD, and non-OD (exudates and noise). Next, an OD boundary is determined and eliminated after applying blob boundary measurement and morphological reconstruction. Finally, exudates are extracted by applying the maximum entropy thresholding to filter out the bright pixels from the green component of retinal image which OD region inside is eliminated. The proposed technique has been tested first on 100 images from hospital. Experimental results show that 93% and 89% of OD and exudate were detected correctly, respectively. © 2013 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Glioma Brain Tumor Classification using Transfer Learning(2024-01-01);