Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries
Advances in computed tomography (CT) have resulted in a substantial increase in the size of datasets. We built a new concept of medical image compression that provides the best compromise between compression rate and image quality. The method is based on multiple contexts and regions-of-interest (RO...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Journal of Cardiovascular Development and Disease |
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| Online Access: | https://www.mdpi.com/2308-3425/9/5/137 |
| _version_ | 1827668428060622848 |
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| author | Guillaume Fahrni David C. Rotzinger Chiaki Nakajo Jamshid Dehmeshki Salah Dine Qanadli |
| author_facet | Guillaume Fahrni David C. Rotzinger Chiaki Nakajo Jamshid Dehmeshki Salah Dine Qanadli |
| author_sort | Guillaume Fahrni |
| collection | DOAJ |
| description | Advances in computed tomography (CT) have resulted in a substantial increase in the size of datasets. We built a new concept of medical image compression that provides the best compromise between compression rate and image quality. The method is based on multiple contexts and regions-of-interest (ROI) defined according to the degree of clinical interest. High priority areas (primary ROIs) are assigned a lossless compression. Other areas (secondary ROIs and background) are compressed with moderate or heavy losses. The method is applied to a whole dataset of CT angiography (CTA) of the lower extremity vasculature. It is compared to standard lossy compression techniques in terms of quantitative and qualitative image quality. It is also compared to standard lossless compression techniques in terms of image size reduction and compression ratio. The proposed compression method met quantitative criteria for high-quality encoding. It obtained the highest qualitative image quality rating score, with a statistically significant difference compared to other methods. The average compressed image size was up to 61% lower compared to standard compression techniques, with a 9:1 compression ratio compared with original non-compressed images. Our new adaptive 3D compression method for CT images can save data storage space while preserving clinically relevant information. |
| first_indexed | 2024-03-10T03:40:37Z |
| format | Article |
| id | doaj.art-90ab56a60de842669b0e78092e258647 |
| institution | Directory Open Access Journal |
| issn | 2308-3425 |
| language | English |
| last_indexed | 2024-03-10T03:40:37Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Cardiovascular Development and Disease |
| spelling | doaj.art-90ab56a60de842669b0e78092e2586472023-11-23T11:32:39ZengMDPI AGJournal of Cardiovascular Development and Disease2308-34252022-04-019513710.3390/jcdd9050137Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral ArteriesGuillaume Fahrni0David C. Rotzinger1Chiaki Nakajo2Jamshid Dehmeshki3Salah Dine Qanadli4Cardiothoracic and Vascular Division, Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, SwitzerlandCardiothoracic and Vascular Division, Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, SwitzerlandCardiothoracic and Vascular Division, Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, SwitzerlandDepartment of Computer Science, Kingston University, Kingston-upon-Thames KT1 2QT, UKCardiothoracic and Vascular Division, Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, SwitzerlandAdvances in computed tomography (CT) have resulted in a substantial increase in the size of datasets. We built a new concept of medical image compression that provides the best compromise between compression rate and image quality. The method is based on multiple contexts and regions-of-interest (ROI) defined according to the degree of clinical interest. High priority areas (primary ROIs) are assigned a lossless compression. Other areas (secondary ROIs and background) are compressed with moderate or heavy losses. The method is applied to a whole dataset of CT angiography (CTA) of the lower extremity vasculature. It is compared to standard lossy compression techniques in terms of quantitative and qualitative image quality. It is also compared to standard lossless compression techniques in terms of image size reduction and compression ratio. The proposed compression method met quantitative criteria for high-quality encoding. It obtained the highest qualitative image quality rating score, with a statistically significant difference compared to other methods. The average compressed image size was up to 61% lower compared to standard compression techniques, with a 9:1 compression ratio compared with original non-compressed images. Our new adaptive 3D compression method for CT images can save data storage space while preserving clinically relevant information.https://www.mdpi.com/2308-3425/9/5/137medical image compressioncomputer aided segmentationimage processingradiologyperipheral artery diseaseCT angiography |
| spellingShingle | Guillaume Fahrni David C. Rotzinger Chiaki Nakajo Jamshid Dehmeshki Salah Dine Qanadli Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries Journal of Cardiovascular Development and Disease medical image compression computer aided segmentation image processing radiology peripheral artery disease CT angiography |
| title | Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries |
| title_full | Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries |
| title_fullStr | Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries |
| title_full_unstemmed | Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries |
| title_short | Three-Dimensional Adaptive Image Compression Concept for Medical Imaging: Application to Computed Tomography Angiography for Peripheral Arteries |
| title_sort | three dimensional adaptive image compression concept for medical imaging application to computed tomography angiography for peripheral arteries |
| topic | medical image compression computer aided segmentation image processing radiology peripheral artery disease CT angiography |
| url | https://www.mdpi.com/2308-3425/9/5/137 |
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