4 results on '"Jung, Hye-Won"'
Search Results
2. Automated detection of circular marker particles in synchrotron phase contrast X-ray images of live mouse nasal airways for mucociliary transit assessment
- Author
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Sang-Heon Lee, Hye-Won Jung, David Parsons, Martin Donnelley, Ivan Lee, Jung, Hye-Won, Lee, Sang-Heon, Donnelley, Martin, Parsons, David, and Lee, Ivan
- Subjects
Materials science ,Transit system ,Phase contrast microscopy ,Early death ,02 engineering and technology ,Tracking (particle physics) ,phase contrast ,01 natural sciences ,law.invention ,cystic fibrosis ,010309 optics ,circle detection ,Artificial Intelligence ,law ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Projection (set theory) ,General Engineering ,Synchrotron ,Computer Science Applications ,edge projection ,X ray image ,Particle ,020201 artificial intelligence & image processing ,sectored ring mask ,Biomedical engineering - Abstract
The non-invasive measurement of mucociliary transit system for CF is required.The automatic circular particles is challenging in Synchrotron X-ray images.A noble method to automatically count the circular shapes is proposed.Robust detection accuracy of 92.7% F-measurement is achieved. Cystic Fibrosis is a genetic disease in which the production of thick sticky mucus compromises the mucociliary transit (MCT) system and causes obstruction of the conducting airways. This results in a cycle of inflammation and infection that dramatically reduces quality of life and causes an early death for most. To directly assess airway health and the effects of potential treatments, synchrotron X-ray imaging techniques have been developed to non-invasively quantify MCT, by visualizing the motion of micron-sized spherical particles deposited into the nasal airways of live mice. Since the level of contrast between the target particles and the background is quite low, and the particles often overlap, most existing methods show a low detection accuracy for the MCT tracking particles in these state-of-the-art PCXI images. This paper proposes a new way to automatically detect the circular shapes of micron-sized particles in these low-contrast X-ray images. The proposed algorithm uses a gradient-directional, sectored ring mask, combined with an edge projection into the ring boundary to identify circular shapes. This new algorithm achieves significantly improved marker particle detection rate, 92.1% precision, 93.9% recall and 92.7% F-measurement, compared to existing methods. It can detect a certain degree of overlapping particles that existing methods struggle to achieve. This algorithm provides automatic MCT particle counting, which significantly reduces the manual labelling process for MCT analysis of living animals.
- Published
- 2017
3. Multiple mucociliary transit marker tracking in synchrotron X-ray images using the global nearest neighbor method
- Author
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Martin Donnelley, Hye-Won Jung, Ivan Lee, Sang-Heon Lee, David Parsons, Jung, Hye-Won, Lee, Ivan, Lee, Sang-Heon, Parsons, David, Donnelley, Martin, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 Jeju Island, and South Korea 11-15 July 2017
- Subjects
Computer science ,False positives and false negatives ,Nearest neighbour algorithm ,Respiratory System ,particle filters ,02 engineering and technology ,Tracking (particle physics) ,law.invention ,Pattern Recognition, Automated ,law ,synchrotrons ,0202 electrical engineering, electronic engineering, information engineering ,Cluster Analysis ,Computer vision ,Transit (satellite) ,business.industry ,Track (disk drive) ,Marker tracking ,X-Rays ,020208 electrical & electronic engineering ,x-ray imaging ,image sequences ,Synchrotron ,X ray image ,020201 artificial intelligence & image processing ,Artificial intelligence ,maintenance engineering ,business ,target tracking ,Algorithms ,Synchrotrons - Abstract
Recent research has enabled in-vivo examination of mucociliary transit in live airways by analysing the movement patterns of micron-sized markers in high resolution synchrotron X-ray images. However, high levels of false positives and false negatives severely impact the performance of many automated tracking algorithms. This paper proposes an improved approach to track valid mucociliary transit markers using a modified gating region and cost matrix. The proposed method offers a more effective way to associate markers with the correct trackers. Improved visualization methods are also introduced to assist the interpretation of the tracking results. The tracking method has achieved a tracking accuracy of 81.7% track purity and 71.3% track effectiveness. Refereed/Peer-reviewed
- Published
- 2017
4. Circular particle detection using sectored ring mask for synchrotron PCXI images
- Author
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Ivan Lee, Sang-Heon Lee, Hye-Won Jung, 37th Annual international conference of IEEE Engineering in medical and biology society, Biomedical engineering Milano, Italy 25/08/2015-29/11/2015, Jung, Hye-Won, Lee, Ivan, and Lee, Sang-Heon
- Subjects
particle ,Cystic Fibrosis ,Respiratory System ,Radiation ,Signal-To-Noise Ratio ,Noise (electronics) ,Edge detection ,law.invention ,cystic fibrosis ,Mice ,Optics ,law ,respiratory function ,Animals ,Humans ,Respiratory function ,False Positive Reactions ,Particle Size ,Physics ,Staining and Labeling ,business.industry ,detection method ,Filter (signal processing) ,Synchrotron ,Microspheres ,Radiography ,Particle ,Gradient descent ,business ,Algorithms ,Synchrotrons - Abstract
Cystic Fibrosis (CF) is a genetic disorder that compromises the respiratory function and the ability of the mucociliary transit (MCT) system. One of the most recent researches introduced a noble method to investigate the progress of the treatment, in which small particles with mostly circular shape injected to the respiratory system and the images were taken using Synchrotron X-ray beam. Since the small particles flow through the respiratory system of the body, the direct observation of MCT measurement will help to understand the progress of the treatment. Identifying the particle is the critical step towards the automatic analysis of the image. However, the objects of interests are usually very small, not perfect circular shape and slightly overlapped from each other with lots of noise due to radiation. This paper proposes a robust and effective detection method of such particles using sectored ring mask (SRM) with gradient descent method. The proposed method extracts strong edges of the particles and the edge line gradients and circle fitting algorithm will filter out invalid edges, resulting in clear particle edge detection. The proposed method has validated through experimental study and presented robust detection rates of 91.9% precision and 89.0%recall. Refereed/Peer-reviewed
- Published
- 2016
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