Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging
Peripheral intravenous (IV) access is an important issue in daily practice in hospital as it is a common practice in the medical field. However, it will be a difficult task if the dorsalhand veins are not clear or obvious for intravenous access. The poor visibility of dorsal vein may result in wrong...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2018
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| Online Access: | http://eprints.usm.my/53579/ http://eprints.usm.my/53579/1/Modified%20Image%20Enhancement%20Algorithm%20For%20Dorsal%20Hand%20Veins%20Imaging_Gan%20Siew%20Ling_E3_2018.pdf |
| _version_ | 1848882568366129152 |
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| author | Gan, Siew Ling |
| author_facet | Gan, Siew Ling |
| author_sort | Gan, Siew Ling |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Peripheral intravenous (IV) access is an important issue in daily practice in hospital as it is a common practice in the medical field. However, it will be a difficult task if the dorsalhand veins are not clear or obvious for intravenous access. The poor visibility of dorsal vein may result in wrong puncturing which causes patient to suffer from pain and even will lead to permanent damage of vein. Hence, a number of imaging methods have been implemented to expose the veins. At present, there are limited literature regarding the specific study to justify the enhancement algorithm which can perform effectively for dorsal hand vein imaging. Therefore, this research is set-up to develop a modified image enhancement
algorithm for dorsal hand vein. Firstly, the grayscale hand vein image obtained from NIR imaging with noise undergoes grayscale enhancement by applying Contrast Limited
Adaptive Histogram Equalization (CLAHE). Then, the adaptive thresholding method is implemented on the filtered grayscale image for vein pattern segmentation purpose. After
image segmentation, the input image is converted to binary image. The noisy binary vein pattern is then enhanced using a combination of Feed-Forward Neural Network (FFNN),
Area Opening (AO) and Binary Median Filter (BMF). Finally, the enhanced image is evaluated by examining the image’s sensitivity, specificity and accuracy of the enhanced
image through comparison with the ground truth images. The evaluation results between modified image enhancement algorithm are compared with the existed algorithm. The evaluation results shows that the AO-FFNN-BMF sequence produces the highest sensitivity, specificity and accuracy for both input images. The proposed technique has produced the clearest vein patterns in terms of connectivity and smoothness than the other binary
enhancement techniques. |
| first_indexed | 2025-11-15T18:36:59Z |
| format | Monograph |
| id | usm-53579 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:36:59Z |
| publishDate | 2018 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-535792022-07-25T07:47:42Z http://eprints.usm.my/53579/ Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging Gan, Siew Ling T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Peripheral intravenous (IV) access is an important issue in daily practice in hospital as it is a common practice in the medical field. However, it will be a difficult task if the dorsalhand veins are not clear or obvious for intravenous access. The poor visibility of dorsal vein may result in wrong puncturing which causes patient to suffer from pain and even will lead to permanent damage of vein. Hence, a number of imaging methods have been implemented to expose the veins. At present, there are limited literature regarding the specific study to justify the enhancement algorithm which can perform effectively for dorsal hand vein imaging. Therefore, this research is set-up to develop a modified image enhancement algorithm for dorsal hand vein. Firstly, the grayscale hand vein image obtained from NIR imaging with noise undergoes grayscale enhancement by applying Contrast Limited Adaptive Histogram Equalization (CLAHE). Then, the adaptive thresholding method is implemented on the filtered grayscale image for vein pattern segmentation purpose. After image segmentation, the input image is converted to binary image. The noisy binary vein pattern is then enhanced using a combination of Feed-Forward Neural Network (FFNN), Area Opening (AO) and Binary Median Filter (BMF). Finally, the enhanced image is evaluated by examining the image’s sensitivity, specificity and accuracy of the enhanced image through comparison with the ground truth images. The evaluation results between modified image enhancement algorithm are compared with the existed algorithm. The evaluation results shows that the AO-FFNN-BMF sequence produces the highest sensitivity, specificity and accuracy for both input images. The proposed technique has produced the clearest vein patterns in terms of connectivity and smoothness than the other binary enhancement techniques. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53579/1/Modified%20Image%20Enhancement%20Algorithm%20For%20Dorsal%20Hand%20Veins%20Imaging_Gan%20Siew%20Ling_E3_2018.pdf Gan, Siew Ling (2018) Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted) |
| spellingShingle | T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Gan, Siew Ling Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title | Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title_full | Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title_fullStr | Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title_full_unstemmed | Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title_short | Modified Image Enhancement Algorithm For Dorsal Hand Veins Imaging |
| title_sort | modified image enhancement algorithm for dorsal hand veins imaging |
| topic | T Technology TK Electrical Engineering. Electronics. Nuclear Engineering |
| url | http://eprints.usm.my/53579/ http://eprints.usm.my/53579/1/Modified%20Image%20Enhancement%20Algorithm%20For%20Dorsal%20Hand%20Veins%20Imaging_Gan%20Siew%20Ling_E3_2018.pdf |