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Kumar PK, Araki T, Rajan J, Laird JR, Nicolaides A, Suri JS. State-of-the-art review on automated lumen and adventitial border delineation and its measurements in carotid ultrasound. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 163:155-168. [PMID: 30119850 DOI: 10.1016/j.cmpb.2018.05.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 04/29/2018] [Accepted: 05/09/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND AND OBJECTIVE Accurate, reliable, efficient, and precise measurements of the lumen geometry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the risk of stroke. The image-based degree of stenosis in the carotid artery and the plaque burden can be predicted using the automated carotid lumen diameter (LD)/inter-adventitial diameter (IAD) measurements from B-mode ultrasound images. The objective of this review is to present the state-of-the-art methods and systems for the measurement of LD/IAD in CCA based on automated or semi-automated strategies. Further, the performance of these systems is compared based on various metrics for its measurements. METHODS The automated algorithms proposed for the segmentation of carotid lumen are broadly classified into two different categories as: region-based and boundary-based. These techniques are discussed in detail specifying their pros and cons. Further, we discuss the challenges encountered in the segmentation process along with its quantitative assessment. Lastly, we present stenosis quantification and risk stratification strategies. RESULTS Even though, we have found more boundary-based approaches compared to region-based approaches in the literature, however, the region-based strategy yield more satisfactory performance. Novel risk stratification strategies are presented. On a patient database containing 203 patients, 9 patients are identified as high risk patients, whereas 27 patients are identified as medium risk patients. CONCLUSIONS We have presented different techniques for the lumen segmentation of the common carotid artery from B-mode ultrasound images and measurement of lumen diameter and inter-adventitial diameter. We believe that the issue regarding boundary-based techniques can be compensated by taking regional statistics embedded with boundary-based information.
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Affiliation(s)
- P Krishna Kumar
- Department of Computer Science and Engineering, National Institute of Technology Calicut, Kerala, India
| | - Tadashi Araki
- Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan
| | - Jeny Rajan
- Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal, India
| | - John R Laird
- Heart and Vascular Institute, Adventist Health, St. Helena, CA, USA
| | | | - Jasjit S Suri
- Stroke Monitoring Division, AtheroPoint, Roseville, CA, USA; Department of Electrical Engineering, University of Idaho (Affl.), ID, USA.
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Araki T, Kumar AM, Krishna Kumar P, Gupta A, Saba L, Rajan J, Lavra F, Sharma AM, Shafique S, Nicolaides A, Laird JR, Suri JS. Ultrasound-Based Automated Carotid Lumen Diameter/Stenosis Measurement and its Validation System. ACTA ACUST UNITED AC 2018. [DOI: 10.1177/154431671604000302] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Objective Degree of carotid stenosis is an important predictor to assess risk of stroke. Systolic velocity-based methods for lumen diameter and stenosis measurement are subjective. Image-based methods face a challenge because of low gradients in media and intima walls. Methods This article presents AtheroEdge™ 2.0, a two-stage process for automated carotid lumen diameter measurement that combats the above challenges. Stage one uses spectral analysis based on the hypothesis that far-wall adventitia is brightest. Stage two uses lumen pixel region identification based on the assumption that blood flow has constant density. Using global and local processing, lumen boundaries are detected. This clinical system outputs lumen diameter along with stenosis severity index (SSI). Results Our database consists of institutional review board–approved 202 patients (males/females: 155/47) left and right common carotid artery images (404 images, Toshiba scanner). Two trained neuro radiologists performed manual lumen border tracings using ImgTracer™ software. The coefficient of correlation between automated and two manual readings was 0.91 and 0.92. Dice similarity and Jaccard index were 95.82%, 95.72% and 92.10%, 91.92%, respectively. The mean diameter error between automated and two manual readings was 0.27 ± 0.26 and 0.26 ± 0.28 mm, respectively. Precision of merit was 98.05% and 99.03% with respect to two readings. SSI showed 97% accuracy. Conclusions The image-based automated carotid lumen diameter and stenosis measurement system is fast, accurate, and reliable.
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Affiliation(s)
- Tadashi Araki
- Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan
| | - Asheed M. Kumar
- Department of Computer Science and Engineering, National Institute of Technology Karnataka, India
- Point-of-Care Devices, Global Biomedical Technologies, Inc., Roseville, California
| | - P. Krishna Kumar
- Department of Computer Science and Engineering, National Institute of Technology Karnataka, India
- Point-of-Care Devices, Global Biomedical Technologies, Inc., Roseville, California
| | - Ajay Gupta
- Radiology Department, Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York
| | - Luca Saba
- Department of Radiology, University of Cagliari, Cagliari, Italy
| | - Jeny Rajan
- Department of Computer Science and Engineering, National Institute of Technology Karnataka, India
- Point-of-Care Devices, Global Biomedical Technologies, Inc., Roseville, California
| | - Francesco Lavra
- Department of Radiology, University of Cagliari, Cagliari, Italy
| | - Aditya M. Sharma
- Division of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia
| | | | | | - John R. Laird
- UC Davis Vascular Center, University of California, Davis, California
| | - Jasjit S. Suri
- Point-of-Care Devices, Global Biomedical Technologies, Inc., Roseville, California
- Monitoring and Diagnostic Division, AtheroPoint™, Roseville, California
- Department of Electrical Engineering, University of Idaho, Moscow, Idaho
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Wivern: a Web-Based System Enabling Computer-Aided Diagnosis and Interdisciplinary Expert Collaboration for Vascular Research. J Med Biol Eng 2017. [DOI: 10.1007/s40846-017-0256-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach. Med Biol Eng Comput 2016; 55:1415-1434. [PMID: 27943087 DOI: 10.1007/s11517-016-1601-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 11/28/2016] [Indexed: 10/20/2022]
Abstract
Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients' left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system.
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Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches. J Med Syst 2016; 40:182. [PMID: 27299355 DOI: 10.1007/s10916-016-0543-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 06/08/2016] [Indexed: 10/21/2022]
Abstract
The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques.
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Saba L, Araki T, Kumar PK, Rajan J, Lavra F, Ikeda N, Sharma AM, Shafique S, Nicolaides A, Laird JR, Gupta A, Suri JS. Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis. JOURNAL OF CLINICAL ULTRASOUND : JCU 2016; 44:210-220. [PMID: 26887355 DOI: 10.1002/jcu.22334] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Revised: 11/27/2015] [Accepted: 12/31/2015] [Indexed: 06/05/2023]
Abstract
PURPOSE To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS). METHODS Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides. RESULTS The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively. CONCLUSIONS Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients.
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Affiliation(s)
- Luca Saba
- Department of Radiology, University of Cagliari, Italy
| | - Tadashi Araki
- Division of Cardiovascular Medicine, Toho University, Ohashi Medical Center, Tokyo, Japan
| | - P Krishna Kumar
- Department of Computer Science and Engineering, National Institute of Technology, Karnataka, India
- Point-of-Care Devices, Global Biomedical Technologies, Inc, Roseville, CA
| | - Jeny Rajan
- Department of Computer Science and Engineering, National Institute of Technology, Karnataka, India
- Point-of-Care Devices, Global Biomedical Technologies, Inc, Roseville, CA
| | | | - Nobutaka Ikeda
- Cardiovascular Medicine, National Center for Global Health and Medicine, Tokyo, Japan
| | - Aditya M Sharma
- Division of Cardiovascular Medicine, Department of Medicine, University of Virginia, VA
| | | | | | - John R Laird
- UC Davis Vascular Center, University of California, Davis, CA
| | - Ajay Gupta
- Radiology Department, Brain and Mind Research Institute, Weill Cornell Medical College, NY
| | - Jasjit S Suri
- Point-of-Care Devices, Global Biomedical Technologies, Inc, Roseville, CA
- Monitoring and Diagnostic Division, AtheroPoint, Roseville, CA
- Department of Electrical Engineering, University of Idaho (Affl.), ID
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Automatic Lumen Detection on Longitudinal Ultrasound B-Mode Images of the Carotid Using Phase Symmetry. SENSORS 2016; 16:s16030350. [PMID: 27005631 PMCID: PMC4813925 DOI: 10.3390/s16030350] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Revised: 03/01/2016] [Accepted: 03/03/2016] [Indexed: 11/17/2022]
Abstract
This article describes a method that improves the performance of previous approaches for the automatic detection of the common carotid artery (CCA) lumen centerline on longitudinal B-mode ultrasound images. We propose to detect several lumen centerline candidates using local symmetry analysis based on local phase information of dark structures at an appropriate scale. These candidates are analyzed with selection mechanisms that use symmetry, contrast or intensity features in combination with position-based heuristics. Several experimental results are provided to evaluate the robustness and performance of the proposed method in comparison with previous approaches. These results lead to the conclusion that our proposal is robust to noise, lumen artifacts, contrast variations and that is able to deal with the presence of CCA-like structures, significantly improving the performance of our previous approach, from 87.5% ± 0.7% of correct detections to 98.3% ± 0.3% in a set of 200 images.
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Dey N, Bose S, Das A, Chaudhuri SS, Saba L, Shafique S, Nicolaides A, Suri JS. Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine. J Med Syst 2016; 40:91. [PMID: 26860914 DOI: 10.1007/s10916-016-0451-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 01/29/2016] [Indexed: 11/29/2022]
Abstract
Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.
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Affiliation(s)
- Nilanjan Dey
- Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India.,Department of Information Technology, Techno India College of Technology, Kolkata, India.,Point of Care Devices, Global Biomedical Technologies, Inc, Roseville, CA, USA
| | - Soumyo Bose
- Department of Information Technology, Techno India College of Technology, Kolkata, India
| | - Achintya Das
- Department of ECE, Kalyani Government Engineering College, Bengal, India
| | - Sheli Sinha Chaudhuri
- Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India
| | - Luca Saba
- Radiology Department, zienda Ospedaliero Universitaria (A.O.U.) di Cagliari, Via Roma, 67, 56126, Pisa, PI, Italy
| | - Shoaib Shafique
- CorVasc Vascular Laboratory, 8433 Harcourt Rd #100, Indianapolis, IN, USA
| | - Andrew Nicolaides
- Vascular Screening and Diagnostic Centre, London, UK.,Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus
| | - Jasjit S Suri
- Point of Care Devices, Global Biomedical Technologies, Inc, Roseville, CA, USA. .,Diagnostic and Monitoring Division, AtheroPoint™ LLC, Roseville, CA, USA. .,Electrical Engineering Department (Affl.), Idaho State University, 921 S 8th Ave, Pocatello, ID, 83201, USA.
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Akkus Z, Carvalho DDB, van den Oord SCH, Schinkel AFL, Niessen WJ, de Jong N, van der Steen AFW, Klein S, Bosch JG. Fully automated carotid plaque segmentation in combined contrast-enhanced and B-mode ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2015; 41:517-531. [PMID: 25542485 DOI: 10.1016/j.ultrasmedbio.2014.10.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 09/29/2014] [Accepted: 10/07/2014] [Indexed: 06/04/2023]
Abstract
Carotid plaque segmentation in B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) is crucial to the assessment of plaque morphology and composition, which are linked to plaque vulnerability. Segmentation in BMUS is challenging because of noise, artifacts and echo-lucent plaques. CEUS allows better delineation of the lumen but contains artifacts and lacks tissue information. We describe a method that exploits the combined information from simultaneously acquired BMUS and CEUS images. Our method consists of non-rigid motion estimation, vessel detection, lumen-intima segmentation and media-adventitia segmentation. The evaluation was performed in training (n = 20 carotids) and test (n = 28) data sets by comparison with manually obtained ground truth. The average root-mean-square errors in the training and test data sets were comparable for media-adventitia (411 ± 224 and 393 ± 239 μm) and for lumen-intima (362 ± 192 and 388 ± 200 μm), and were comparable to inter-observer variability. To the best of our knowledge, this is the first method to perform fully automatic carotid plaque segmentation using combined BMUS and CEUS.
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Affiliation(s)
- Zeynettin Akkus
- Department of Biomedical Engineering, Thoraxcenter, Erasmus MC, Rotterdam, The Netherlands
| | - Diego D B Carvalho
- Departments of Medical Informatics & Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands
| | | | - Arend F L Schinkel
- Department of Cardiology, Thoraxcenter, Erasmus MC, Rotterdam, The Netherlands
| | - Wiro J Niessen
- Departments of Medical Informatics & Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands; Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Nico de Jong
- Department of Biomedical Engineering, Thoraxcenter, Erasmus MC, Rotterdam, The Netherlands; Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Antonius F W van der Steen
- Department of Biomedical Engineering, Thoraxcenter, Erasmus MC, Rotterdam, The Netherlands; Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Stefan Klein
- Departments of Medical Informatics & Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands
| | - Johan G Bosch
- Department of Biomedical Engineering, Thoraxcenter, Erasmus MC, Rotterdam, The Netherlands.
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A review of ultrasound common carotid artery image and video segmentation techniques. Med Biol Eng Comput 2014; 52:1073-93. [PMID: 25284219 DOI: 10.1007/s11517-014-1203-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2013] [Accepted: 09/22/2014] [Indexed: 10/24/2022]
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