Fast Localization of the Optic Disc Using Projection of Image Features / (Record no. 8788)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 10437nam a22002417a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210111b2010 a|||f mb|| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | EG-CaNU |
| Transcribing agency | EG-CaNU |
| 041 0# - Language Code | |
| Language code of text | eng |
| Language code of abstract | eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 610 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ahmed Mohamed Essam Mahfouz |
| 245 1# - TITLE STATEMENT | |
| Title | Fast Localization of the Optic Disc Using Projection of Image Features / |
| Statement of responsibility, etc. | Ahmed Mohamed Essam Mahfouz |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 93 p. |
| Other physical details | ill. |
| Dimensions | 21 cm. |
| 500 ## - GENERAL NOTE | |
| Materials specified | Supervisor: Ahmed Fahmy |
| 502 ## - Dissertation Note | |
| Dissertation type | Thesis (M.A.)—Nile University, Egypt, 2010 . |
| 504 ## - Bibliography | |
| Bibliography | "Includes bibliographical references" |
| 505 0# - Contents | |
| Formatted contents note | Contents:<br/>1. Introduction ......................................................................................................................................... 1<br/>1.1. Objectives .................................................................................................................................... 5<br/>1.2. Motivation ................................................................................................................................... 5<br/>1.3. Arrangement of thesis ................................................................................................................... 5<br/>2. The Retina ............................................................................................................................................ 6<br/>2.1. Anatomy of the Eye ...................................................................................................................... 6<br/>2.1.1. The Retina ........................................................................................................................... 7<br/>2.1.2. The Optic Disc .................................................................................................................... 8<br/>2.1.3. The Macula ......................................................................................................................... 8<br/>2.2. Diabetic Retinopathy .................................................................................................................... 9<br/>2.3. Examining the Retina ................................................................................................................. 11<br/>2.3.1. Fluorescein Angiography .................................................................................................. 12<br/>2.3.2. Optical Coherence Tomography ....................................................................................... 13<br/>2.3.3. Color Fundus Photography ............................................................................................... 15<br/>3. Automatic OD Localization Methods ............................................................................................... 17<br/>3.1. Region of Interest Extraction ...................................................................................................... 17<br/>3.2. Appearance-based Methods ........................................................................................................ 19<br/>3.2.1. Variance-Based Method.................................................................................................... 19<br/>3.2.2. Largest Bright Object ........................................................................................................ 21<br/>3.2.3. Hough Transform .............................................................................................................. 22<br/>3.2.4. Pyramidal Decomposition ................................................................................................. 24<br/>3.2.5. Template Matching-Based Method ................................................................................... 25<br/>3.2.6. Principal Component Analysis ......................................................................................... 26<br/>3.3. Model-based Methods ................................................................................................................<br/>3.3.1. Fuzzy Convergence ........................................................................................................... 27<br/>3.3.2. Vasculature Fitting on a geometrical Model ..................................................................... 30<br/>3.3.3. Vessel‘s Direction Matched Filter .................................................................................... 32<br/>3.3.4. Detecting the Branch with the Most Vessels .................................................................... 34<br/>3.4. Hybrid Methods .......................................................................................................................... 37<br/>3.4.1. Binary Vasculature with the Hough Transform ................................................................ 37<br/>3.4.2. Fuzzy Convergence with the Hough Transform ............................................................... 48<br/>4. Fast Localization of the OD ............................................................................................................... 40<br/>4.1. Theory ........................................................................................................................................ 40<br/>4.1.1. Projection of Image Features ............................................................................................ 40<br/>4.1.2. Selecting Features ............................................................................................................. 42<br/>4.2. Methods ..................................................................................................................................... 46<br/>4.2.1. OD Localization ................................................................................................................ 46<br/>4.2.2. Improving the Robustness ................................................................................................ 49<br/>4.3. Algorithm................................................................................................................................... 53<br/>5. Evaluation and Results ...................................................................................................................... 54<br/>5.1. Databases ................................................................................................................................... 54<br/>5.1.1. STARE Database .............................................................................................................. 55<br/>5.1.2. DRIVE Database ............................................................................................................... 56<br/>5.1.3. DIARETDB0 and DIARETDB1 ...................................................................................... 57<br/>5.2. Experiments ............................................................................................................................... 58<br/>5.2.1. Algorithm Parameters ....................................................................................................... 58<br/>5.2.2. Evaluation Criteria ............................................................................................................ 59<br/>5.3. Results ....................................................................................................................................... 62<br/>6. Discussion and Future Work ............................................................................................................. 68<br/>6.1. Discussion ..................................................................................................................................... 68<br/>6.2. Future Work .................................................................................................................................. 72<br/>Appendix: Hough Transform and Template Matching for OD Localization ..................................... 73<br/>A.1. OD Localization using Hough Transform .................................................................................... 73<br/>A.2. OD Localization using Template Matching ................................................................................. 76<br/>A.3. Hough Transform vs. Template Matching .................................................................................... 78<br/>Bibliography ........................ |
| 520 3# - Abstract | |
| Abstract | Abstract:<br/>Diabetic Retinopathy, one of the complications caused by diabetes, causes a large number of new cases of blindness each year. The risk of visual disabilities and blindness due to diabetic retinopathy could be greatly minimized by early diagnosis. Consequently, the need for mass-screening of diabetic patients‘ eyes is clearly a vital concern. With the new advances in digital modalities for retinal imaging, an ophthalmologist needs to examine a large number of retinal images to diagnose each patient. Therefore, there is a significant need to develop Computer-Assisted Diagnostic tools for automatic retinal image analysis.<br/>Optic disc localization is an important pre-processing step that significantly simplifies subsequent segmentation of the optic disc and other retinal structures. Moreover, optic disc localization is very useful for a number of applications other than segmentation of a retinal image; such as: registration, image orientation classification and vessels tracking. Current automatic optic disc localization techniques suffer from impractically-high computation times (few minutes per image). In this thesis, we present a fast technique that requires less than a second to localize the optic disc. The technique is based on obtaining two projections of certain image features that encode the x- and y- coordinates of the optic disc. The resulting 1D projections are then searched to determine the location of the optic disc. This avoids searching the 2D image space and thus enhances the speed of the optic disc localization process. Image features such as retinal vessels orientation and the optic disc brightness are used in the current method. Four publicly-available databases, including STARE and DRIVE, are used to evaluate the proposed technique. The optic disc was successfully located in 330 images out of 340 images (97%) with the computation time less than a second per image for different resolutions. |
| 546 ## - Language Note | |
| Language Note | Text in English, abstracts in English. |
| 650 #4 - Subject | |
| Subject | Informatics-IFM |
| 655 #7 - Index Term-Genre/Form | |
| Source of term | NULIB |
| focus term | Dissertation, Academic |
| 690 ## - Subject | |
| School | Informatics-IFM |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Thesis |
| 650 #4 - Subject | |
| -- | 266 |
| 655 #7 - Index Term-Genre/Form | |
| -- | 187 |
| 690 ## - Subject | |
| -- | 266 |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Date acquired | Total Checkouts | Full call number | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Not For Loan | Main library | Main library | 01/11/2021 | 610/ AM.F 2010 | 01/11/2021 | 01/11/2021 | Thesis |