Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach
Bronchiectasis in children is a major health issue which can be life-threatening if not diagnosed and effectively treated. In the diagnosis of bronchiectasis, an increased broncho-arterial (BA) ratio is considered a significant marker. The BA ratio is measured by evaluating BA pairs, using high-reso...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-11-01
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| Series: | Intelligent Systems with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305323001047 |
| _version_ | 1827686945103282176 |
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| author | Sami Azam Sidratul Montaha A.K.M. Rakibul Haque Rafid Asif Karim Mirjam Jonkman Friso De Boer Gabrielle McCallum Ian Brent Masters Anne B Chang |
| author_facet | Sami Azam Sidratul Montaha A.K.M. Rakibul Haque Rafid Asif Karim Mirjam Jonkman Friso De Boer Gabrielle McCallum Ian Brent Masters Anne B Chang |
| author_sort | Sami Azam |
| collection | DOAJ |
| description | Bronchiectasis in children is a major health issue which can be life-threatening if not diagnosed and effectively treated. In the diagnosis of bronchiectasis, an increased broncho-arterial (BA) ratio is considered a significant marker. The BA ratio is measured by evaluating BA pairs, using high-resolution computed tomography (HRCT) scans. Detecting BA pairs automatically is challenging due to the complex characteristics of BA pairs and the ambiguous appearance of the bronchi. This study proposes an effective computerized approach to detect BA pairs and assess BA ratio using HRCT scans of children and employing computer-aided techniques and novel custom-build algorithms. Attention is given to reconstructing broken bronchial walls and identifying discrete BA pairs using custom-built kernel based and patch-based algorithms for pixel-level image analysis. To detect BA pairs, the lung region is segmented in the HRCT slices and image preprocessing techniques, including noise reduction, binarizing, largest contour detection and a hole-filling algorithm, are applied. A histogram analysis method is introduced to clean the images. A kernel-based algorithm is proposed to reconstruct the pixel distribution if the bronchial wall is so that the bronchi can be detected precisely. Potential arteries are detected using balanced histogram thresholding, morphological opening and an approach based on four conditions related to the object area circularity, rectangular boundary box ratio and enclosing circle area ratio. Potential bronchi are detected through matching of object coordinates with potential arteries, hole-filling and four condition based approaches. The potential BA pairs are detected by matching the coordinates of potential bronchi with those of potential arteries as the artery and bronchus are adjacent to each other in BA pairs. Finally, from the potential BA pairs, actual BA pairs are identified using a custom-built patch algorithm. The study is conducted using 2471 HRCT slices of seven children, obtained from the Royal Darwin Hospital, Australia. The BA ratio is derived based on the ratio of diameters, major axis lengths, minor axis lengths, area, convex hull and equivalent diameter where the BA ratios are respectively 0.51–0.65, 0.49–0.59, 0.59–0.77, 0.25–0.42, 0.29–0.47, 1.5–2 and 0.50–0.65. |
| first_indexed | 2024-03-10T09:25:46Z |
| format | Article |
| id | doaj.art-856bcd10a969402faf35254bbaa23cec |
| institution | Directory Open Access Journal |
| issn | 2667-3053 |
| language | English |
| last_indexed | 2024-03-10T09:25:46Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Intelligent Systems with Applications |
| spelling | doaj.art-856bcd10a969402faf35254bbaa23cec2023-11-22T04:49:36ZengElsevierIntelligent Systems with Applications2667-30532023-11-0120200279Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approachSami Azam0Sidratul Montaha1A.K.M. Rakibul Haque Rafid2Asif Karim3Mirjam Jonkman4Friso De Boer5Gabrielle McCallum6Ian Brent Masters7Anne B Chang8Faculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, Australia; Corresponding author.Faculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, AustraliaFaculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, AustraliaFaculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, AustraliaFaculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, AustraliaFaculty of Science and Technology, Charles Darwin University, Casuarina, 0909 NT, AustraliaChild Health Division, Menzies School of Health Research, Darwin, Northern Territory, AustraliaAustralian Centre for Health Services Innovation, Queensland University of Technology, Brisbane, Queensland, Australia; Respiratory and Sleep Medicine, Queensland Children's Hospital, South Brisbane, Queensland, AustraliaChild Health Division, Menzies School of Health Research, Darwin, Northern Territory, Australia; Australian Centre for Health Services Innovation, Queensland University of Technology, Brisbane, Queensland, Australia; Respiratory and Sleep Medicine, Queensland Children's Hospital, South Brisbane, Queensland, AustraliaBronchiectasis in children is a major health issue which can be life-threatening if not diagnosed and effectively treated. In the diagnosis of bronchiectasis, an increased broncho-arterial (BA) ratio is considered a significant marker. The BA ratio is measured by evaluating BA pairs, using high-resolution computed tomography (HRCT) scans. Detecting BA pairs automatically is challenging due to the complex characteristics of BA pairs and the ambiguous appearance of the bronchi. This study proposes an effective computerized approach to detect BA pairs and assess BA ratio using HRCT scans of children and employing computer-aided techniques and novel custom-build algorithms. Attention is given to reconstructing broken bronchial walls and identifying discrete BA pairs using custom-built kernel based and patch-based algorithms for pixel-level image analysis. To detect BA pairs, the lung region is segmented in the HRCT slices and image preprocessing techniques, including noise reduction, binarizing, largest contour detection and a hole-filling algorithm, are applied. A histogram analysis method is introduced to clean the images. A kernel-based algorithm is proposed to reconstruct the pixel distribution if the bronchial wall is so that the bronchi can be detected precisely. Potential arteries are detected using balanced histogram thresholding, morphological opening and an approach based on four conditions related to the object area circularity, rectangular boundary box ratio and enclosing circle area ratio. Potential bronchi are detected through matching of object coordinates with potential arteries, hole-filling and four condition based approaches. The potential BA pairs are detected by matching the coordinates of potential bronchi with those of potential arteries as the artery and bronchus are adjacent to each other in BA pairs. Finally, from the potential BA pairs, actual BA pairs are identified using a custom-built patch algorithm. The study is conducted using 2471 HRCT slices of seven children, obtained from the Royal Darwin Hospital, Australia. The BA ratio is derived based on the ratio of diameters, major axis lengths, minor axis lengths, area, convex hull and equivalent diameter where the BA ratios are respectively 0.51–0.65, 0.49–0.59, 0.59–0.77, 0.25–0.42, 0.29–0.47, 1.5–2 and 0.50–0.65.http://www.sciencedirect.com/science/article/pii/S2667305323001047Broncho-arterial pairBroncho-arterial ratioImage processingHRCT scansLung segmentation |
| spellingShingle | Sami Azam Sidratul Montaha A.K.M. Rakibul Haque Rafid Asif Karim Mirjam Jonkman Friso De Boer Gabrielle McCallum Ian Brent Masters Anne B Chang Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach Intelligent Systems with Applications Broncho-arterial pair Broncho-arterial ratio Image processing HRCT scans Lung segmentation |
| title | Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach |
| title_full | Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach |
| title_fullStr | Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach |
| title_full_unstemmed | Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach |
| title_short | Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach |
| title_sort | pixel level image analysis to derive the broncho artery ba ratio employing hrct scans a computer aided approach |
| topic | Broncho-arterial pair Broncho-arterial ratio Image processing HRCT scans Lung segmentation |
| url | http://www.sciencedirect.com/science/article/pii/S2667305323001047 |
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