A hybrid approach for hemorrhage segmentation in pelvic CT scans
DOI: 10.1109/BIBMW.2011.6112428 Conference: 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), Atlanta, GA, USA, November 12-15, 2011
Hemorrhage is the leading cause of death in patients with severe pelvic fractures within the first 24 hours after the injury. Hence, it is vital for physicians to quickly identify hemorrhage and assess bleeding severity. However, it is rather time consuming for physicians to evaluate all the CT images. Therefore, an automated hemorrhage segmentation system is needed to assist physicians. This paper proposes a hybrid approach for hemorrhage segmentation from pelvic CT scans. This approach utilizes region growing technique with integration of contrast information from the previous and subsequent slices. The results show that the method is able to segment hemorrhage well with acceptable results. Hemorrhage volume is also determined. A statistical t-test is conducted to determine if the calculated hemorrhage volume using the proposed method is significantly different from the manually detected volume.
Available from: Ashwin Belle
- "The signal processing system, developed by Shandillya et al., detects the ideal time to defibrillate patients undergoing cardiac arrest or ventricular fibrillation [21, 37]. Davaluri et al. proposes an image processing system which uses CT images of patients with pelvic injuries to produce a quantitative and qualitative assessment of detected hemorrhaging . Similarly, Wu's work on developing a computer-assisted fracture detection system automatically processes several CT slices of pelvic injury patients to identify and quantify potential fractures . "
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ABSTRACT: The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest.
The Scientific World Journal 02/2013; 2013(1):769639. DOI:10.1155/2013/769639 · 1.73 Impact Factor
Available from: Kayvan Najarian
- "They are removed by using morphologic operations. After the filtration of unwanted objects, the region in the image that falls within the gray-level range of arteries is considered as hemorrhage and its center coordinates are identified as the centroid of the hemorrhage region  . The hemorrhage detected may not be the complete region of hemorrhage especially during the veinal phase. "
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ABSTRACT: Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising.
Computational and Mathematical Methods in Medicine 07/2012; 2012(6):898430. DOI:10.1155/2012/898430 · 0.77 Impact Factor
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