Denoising and Enhancement of Medical Images / (Record no. 615842)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03281nam a22001697a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.1,SAA |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Saadia, Ayesha |
| 9 (RLIN) | 35416 |
| 245 ## - TITLE STATEMENT | |
| Title | Denoising and Enhancement of Medical Images / |
| Statement of responsibility, etc. | Ayesha Saadia |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Rawalpindi, |
| Name of publisher, distributor, etc. | MCS (NUST), |
| Date of publication, distribution, etc. | April 2017 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xiv, 77 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Medical imaging captures visual representation of human body’s structural and functional<br/>aspects like tissues, bones, blood flow etc. for clinical analysis and medical intervention.<br/>Optical Imaging, X-ray, Computer tomography, Magnetic Resonance Imaging (MRI), Ultrasound<br/>etc. are common medical imaging techniques used by physicians. Among them ultrasound<br/>is the most widely used imaging technique due to its cost effectiveness and human<br/>health friendly characteristic. But ultrasound images are inherently corrupted with speckle<br/>noise and thus makes physician’s interpretation complex and time-consuming. Therefore, in<br/>medical image analysis image denoising has more clinical value since it helps the physicians<br/>to reach correct, reliable and speedy diagnosis by mitigating noise from the image. Image<br/>denoising also facilitate image segmentation, image fusion, object detection and target<br/>recognition. Computer-aided image denoising and image enhancement techniques helps to<br/>improve efficiency and accuracy of physician’s interpretation.<br/>This research work focused on the development of reliable image denoising and enhancement<br/>techniques for echocardiographic images. It aimed to denoise an echocardiographic<br/>image without introducing noise distortion and loss of information. Fractional calculus has<br/>been used to efficiently mitigate noise of various levels from the echocardiographic image.<br/>Also rough set theory and fuzzy logic have been used to draw boundaries between image<br/>regions. These concepts helped to handle uncertainty caused by the speckle noise. Three<br/>image denoising methods have been proposed in thesis. First proposed denoising methodology<br/>performs image denoising in two stages. Stage-1 applies weighted fuzzy mean filter<br/>and stage-2 convolves every pixel of the image with a fractional integration filter. Second<br/>proposed approach intelligently selects appropriate filter for every image region. Fractional<br/>order differintegral filter is proposed in third image denoising methodology. All three proposed<br/>denoising schemes not only preserve details in the denoised image but also efficiently<br/>reduce noise. Image Enhancement further improves the visual quality of an image. This<br/>research also proposes two echocardiographic image enhancement schemes to effectively<br/>utilize gradient magnitude and eigenvalue hessian matrix calculations and fractional order<br/>derivative concept.<br/>Real echocardiographic b-mode images and standard images artificially corrupted with<br/>speckle noise have been considered in simulations for this research. Visual and quantitative<br/>analysis of simulation results presents significant improvement by the proposed schemes as<br/>compared to state-of-the art image denoising and image enhancement techniques. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | PhD Computer Software Engineering Thesis |
| 9 (RLIN) | 132801 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Source of heading or term | |
| Geographic name | PhD CSE Thesis |
| 9 (RLIN) | 132802 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervised by Dr. Adnan Rashdi |
| 9 (RLIN) | 132269 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Public note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 01/17/2026 | 005.1,SAA | MCSPhD CS-03 | 01/17/2026 | 01/17/2026 | Thesis | Almirah No.68, Shelf No.5 |