Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics
| Format: | Restricted Document |
|---|
| _version_ | 1860799612210642944 |
|---|---|
| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 |
| date | 2014-09-11 10:06:01 |
| eventvenue | Japan |
| format | Restricted Document |
| id | 6685 |
| institution | UniSZA |
| originalfilename | 0358-01-FH03-FIK-15-02473.jpg |
| person | UniSZA Unisza unisza |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6685 |
| spelling | 6685 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6685 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper UniSZA Unisza unisza image/jpeg inches 96 96 2014-09-11 10:06:01 792 1420x792 1420 01 01 0358-01-FH03-FIK-15-02473.jpg UniSZA Private Access Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics We propose a new extract on method of the macular disease area in the human retinal layer from OCT images using three dimensional regional statistics. In previous researches, we extracted disease area by using the mean and standard deviation of the two dimensional disease part pointed out by a clinical doctor. However, the previous method cannot extract disease area for some disease OCT images precisely. In this paper, we propose a new extraction method of the disease area using three dimensional regional statistics. We use a set of 128 images (3D-0CT image) consisted of 2 dimensional OCT retinal image about one retina of a patient. The regional mean and regional standard deviation of gray level are calculated in the three dimensional region of interest (ROI, 125 (=5 x 5 x 5) pixels) in the abnormal area pointed by a clinical doctor. These values are compared with every ROI in the abnormal area to extract the disease area, and the proposal system measures the volume of the disease area. We apply the proposed method to OCT images of 5 patients with retinal diseases. As a result. we can measure the volume of the abnormal area with 80.7% average accuracy. 17th kes2013 Japan |
| spellingShingle | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| summary | We propose a new extract on method of the macular disease area in the human retinal layer from OCT images using three dimensional regional statistics. In previous researches, we extracted disease area by using the mean and standard deviation of the two dimensional disease part pointed out by a clinical doctor. However, the previous method cannot extract disease area for some disease OCT images precisely. In this paper, we propose a new extraction method of the disease area using three dimensional regional statistics. We use a set of 128 images (3D-0CT image) consisted of 2 dimensional OCT retinal image about one retina of a patient. The regional mean and regional standard deviation of gray level are calculated in the three dimensional region of interest (ROI, 125 (=5 x 5 x 5) pixels) in the abnormal area pointed by a clinical doctor. These values are compared with every ROI in the abnormal area to extract the disease area, and the proposal system measures the volume of the disease area. We apply the proposed method to OCT images of 5 patients with retinal diseases. As a result. we can measure the volume of the abnormal area with 80.7% average accuracy. |
| title | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| title_full | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| title_fullStr | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| title_full_unstemmed | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| title_short | Extraction of disease area from retinal optical coherence tomography images using three dimensional regional Statistics |
| title_sort | extraction of disease area from retinal optical coherence tomography images using three dimensional regional statistics |