98 research outputs found
๋ฌผ์ง ํผํฉ๋น์จ๊ณผ ๊ตฌ์กฐ์ ํน์ง์ ํตํฉ ์ฌ๊ตฌ์ฑ ๋ชจ๋ธ์ ์ด์ฉํ ์ ์์ ์ฅ์ธ์ฒ ๊ธฐ๋ฒ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ ๊ธฐยท์ปดํจํฐ๊ณตํ๋ถ, 2013. 8. ์ ์๊ธธ.๋์ฅ ์ปดํจํฐ ๋จ์ธต ์ดฌ์ ์์์์ ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ์ ์ ๊ฑฐํ๊ธฐ ์ํด ์ ์์ ์ฅ์ธ์ฒ ๋ฐฉ๋ฒ์ด ์ด์ฉ๋๋ค. ๋ณธ ๋
ผ๋ฌธ์์๋ ์ ์์ ์ฅ์ธ์ฒ ๋ฐฉ๋ฒ์์ ๊ฒฐํจ์ ์ฃผ์ ์์ธ์ด ๋๋ ๋ถ๋ถ ์ฉ์ ํจ๊ณผ์ ๊ฐ์ฑ ์์น ํจ๊ณผ๋ฅผ ๋์์ ํด๊ฒฐํ๊ธฐ ์ํด ๋ฌผ์ง ํผํฉ๋น์จ๊ณผ ๊ตฌ์กฐ์ ํน์ง์ ํตํฉ ์ฌ๊ตฌ์ฑ ๋ชจ๋ธ์ ์ด์ฉํ ์ ์์ ์ฅ์ฒญ์ ๊ธฐ๋ฒ์ ์ ์ํ๋ค. ๋จผ์ ๋์ฅ ์ปดํจํฐ ๋จ์ธต ์ดฌ์ ์์์์ ๊ณต๊ธฐ, ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ, ๊ณต๊ธฐ์ ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ ์ฌ์ด์ ๊ฒฝ๊ณ (๊ณต๊ธฐ-์์ฌ๋ฌผ ๊ฒฝ๊ณ), ๋์ฅ์ธ๋ถ์ ์ฐ์กฐ์ง๊ณผ ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ ์ฌ์ด์ ๊ฒฝ๊ณ (์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ), ๊ทธ๋ฆฌ๊ณ ๊ณต๊ธฐ, ์ฐ์กฐ์ง, ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ์ด ๋ง๋๋ ๊ฒฝ๊ณ (๊ณต๊ธฐ-์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ) ์์ญ์ ํฌํจํ ๊ฒฐ์ฅ ์์๋ฅผ ๋ถํ ํ๋ค. ๋ถํ ๋ ๊ณต๊ธฐ์ ๊ณต๊ธฐ-์์ฌ๋ฌผ ๊ฒฝ๊ณ ์์ญ์ ๋ํด์๋ ๊ฐ ๋ณต์
์ ๋ฐ๋๊ฐ์ ๋์ผํ๊ฒ ๊ณต๊ธฐ์ ๋ํ ๋ฐ๋๊ฐ์ผ๋ก ๋์ฒดํจ์ผ๋ก์จ ์์ฌ๋ฌผ์ ์ ๊ฑฐํ๋ค. ๋ฐ๋ฉด์ ๋ถํ ๋ ์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ์ ๊ณต๊ธฐ-์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ ์์ญ์ ๋ํด์๋ ๋ฌผ์ง ํผํฉ๋น์จ๊ณผ ๊ตฌ์กฐ์ ํน์ง์ ๊ณ์ฐํ๋ค. ๋ฌผ์ง ํผํฉ๋น์จ์ ๋ ๋ฌผ์ง๊ฐ ํน์ ์ธ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์ ์ด์ฉํ์ฌ ์์ธกํ๊ณ ๊ตฌ์กฐ์ ํน์ง์ ํค์์ ํ๋ ฌ์ ์์ด๊ฒ ๋ถ์์ ๊ธฐ๋ฐํ์ฌ ๊ณ์ฐํ๋ค. ๊ณ์ฐ๋ ๋ฌผ์ง ํผํฉ๋น์จ๊ณผ ๊ตฌ์กฐ์ ํน์ง์ ์ด์ฉํ์ฌ ์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ์ ๊ณต๊ธฐ-์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ ์์ญ์ ์ํ๋ ๊ฐ ๋ณต์
์ ๋ฐ๋๊ฐ์ด ์ฌ๊ตฌ์ฑ๋๋ค. ๋ฌผ์ง ํผํฉ๋น์จ๊ณผ ๊ตฌ์กฐ์ ํน์ง์ ํตํฉ ์ฌ๊ตฌ์ฑ ๋ชจ๋ธ์ ๊ฐ ๋ณต์
๋ด์ ์ฐ์กฐ์ง์ ๋ถ๋ถ ์ฉ์ ์ ์ ์ง์ํค๋ ๋์์ ์กฐ์ ์ฒ๋ฆฌ๋ ์์ฌ๋ฌผ์ ๊ฐ์ฑ ์์น ํจ๊ณผ๋ก ์ธํด ์ฝํ๋ ์์ฌ๋ฌผ์ ์ ๊ธด ๋์ฅ ์ฃผ๋ฆ ๋ฐ ์ฉ์ข
์ด ๋ณด์กด๋ ์ ์๋๋ก ํ๋ค. ๋ฐ๋ผ์ ์ ์๋ ์ ์์ ์ฅ์ธ์ฒ ๋ฐฉ๋ฒ์์๋ ๋ถ๋ถ ์ฉ์ ํจ๊ณผ๋ก ์ธํ ์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ์ ๊ณ๋จ๋ฌด๋ฌ ๊ฒฐํจ๊ณผ ๊ฐ์ฑ ์์น ํจ๊ณผ๋ก ์ธํ ์์ฌ๋ฌผ์ ์ ๊ธด ๋์ฅ ์ฃผ๋ฆ ๋ฐ ์ฉ์ข
์ ์ง๋์น ์ธ์ฒ ๊ฒฐํจ์ ํผํ ์ ์๋ค. ๋ํ ๋ณธ ๋
ผ๋ฌธ์์๋ ๊ธฐ์กด ์ธ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์ ์ฐ์ฐ ๋ณต์ก๋๋ฅผ ์ค์ด๊ธฐ ์ํด ๋จ์ ์ธ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์ ์ ์ํ๋ค. ๋จ์ ์ธ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์์๋ ๋ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์ ๋ฐ๋ณต ์ ์ฉ์ํด์ผ๋ก์จ ์ป์ด์ง ์ธ ์์ (๊ณต๊ธฐ-์ฐ์กฐ์ง, ๊ณต๊ธฐ-์์ฌ๋ฌผ, ์ฐ์กฐ์ง-์์ฌ๋ฌผ) ๋ ๋ฌผ์ง๊ฐ ํผํฉ๋น์จ์ ๊ตฌํ๊ณ ์ด๋ฅผ ์ผ๊ฐํ์ ์ด์ฉํ ๋ฌด๊ฒ์ค์ฌ์ขํ ์์์์ ๋ณด๊ฐ๋ฐฉ๋ฒ์ ์ด์ฉํด ํ๋์ ์ธ ๋ฌผ์ง๊ฐ ํผํฉ๋น์จ๋ก ๋ณํํ๋ค. ์ด๊ฐ์ ์์ ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํ์ฌ ์ ์ํ ์ ์์ ์ฅ์ธ์ฒ ๋ฐฉ๋ฒ์ ์ฑ๋ฅ์ ํ๊ฐํ์๋ค. ๋ฐฉ์ฌ์ ์ ๋ฌธ์์ ์ํ ์ฅ์ธ์ฒ ํ์ง ํ๊ฐ์์ ์ ์ ๋ฐฉ๋ฒ์ด ๋ฌผ์ง ํผํฉ๋น์จ์ ์ด์ฉํ ๊ธฐ์กด ๋ฐฉ๋ฒ์ ๋นํด ๋ ๋์ ์ ์์ ์ฅ์ธ์ฒ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์์ผ๋ฉฐ, ํนํ ์์ฌ๋ฌผ์ ์ ๊ธด ๋์ฅ ์ฃผ๋ฆ ๋ฐ ์ฉ์ข
์ด ๋ ์ ๋ณด์กด๋๋ ๊ฒ์ ํ์ธํ์๋ค. ์ด๋ฌํ ๊ฒฐ๊ณผ๋ ์์ฌ๋ฌผ์ ์ ๊ธด ๋์ฅ ์ฃผ๋ฆ ์์ญ์ ์๋ ๋ถํ ํ์ฌ ์ ์ ๋ฐฉ๋ฒ๊ณผ ๊ธฐ์กด ๋ฐฉ๋ฒ์ ์ํ ์ฅ์ธ์ฒ ๊ฒฐ๊ณผ ์์์์ ํด๋น ์์ญ์ ํ๊ท ๋ฐ๋๊ฐ๊ณผ ์ฃผ๋ฆ ๋ณด์กด ๋น์จ์ ๋น๊ตํ ๊ฒฐ๊ณผ์์๋ ๋ง์ฐฌ๊ฐ์ง๋ก ์
์ฆ๋์๋ค. ๋ํ ๊ธฐ์กด์ ๋ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ๋ก๋ ์ ํด๊ฒฐ๋์ง ์์๋ ๊ณต๊ธฐ-์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ ์์ญ์์์ ์ฐ๋ฑ์ฑ์ด ํํ์ ๊ฒฐํจ์ ๋ํด์๋ ์ ์ ๋ฐฉ๋ฒ์์๋ ๋จ์ ์ธ ๋ฌผ์ง๊ฐ ์ ์ด ๋ชจ๋ธ์ ์ด์ฉํ์ฌ ๊ณต๊ธฐ-์ฐ์กฐ์ง-์์ฌ๋ฌผ ๊ฒฝ๊ณ ์์ญ์์์ ๊ฒฐํจ์ ์ ๊ฑฐํ๊ณ ์ ์ฒด ๋์ฅ์ ํ๋ฉด์ด ๊นจ๋ํ๊ฒ ์ฌ๊ตฌ์ฑ๋๋ ๊ฒ์ ํ์ธํ์๋ค.Electronic cleansing (EC) is the process of virtually cleansing the colon by removal of the tagged materials (TMs) in computed tomographic colonography (CTC) images and generating electronically cleansed images. We propose an EC method using a novel reconstruction model. To mitigate partial volume (PV) and pseudo-enhancement (PEH) effects simultaneously, material fractions and structural responses are integrated into a single reconstruction model. In our approach, colonic components including air, TM, interface layer between air and TM (air-TM interface) and interface layer between soft-tissue (ST) and TM (ST-TM interface), and T-junction (i.e., locations where air-TM interface with the colon wall) are first segmented. For each voxel in the segmented TM and air-TM interface, CT density value is replaced with the pure material density of air and thus the unexpected ST-like layers at the air-TM interface (caused by PV effect) are simply removed. On the other hand, for each voxel in the segmented ST-TM interface and T-junction, the two- and three-material fractions at the voxel are derived using a two- and three-material transition models, respectively. For each voxel in the segmented ST-TM interface and T-junction, the structural response is also calculated by rut- and cup-enhancement functions based on the eigenvalue signatures of the Hessian matrix. Then, CT density value of each voxel in ST-TM interface and T-junction is reconstructed based on both the material fractions and structural responses to conserve the PV contributions of ST in the voxel and preserve the folds and polyps submerged in TMs. Therefore, in our ST-preserving reconstruction model, the material fractions remove the aliasing artifacts at the ST-TM interface (caused by PV effect) effectively while the structural responses avoid the erroneous cleansing of the submerged folds and polyps (caused by PEH effect). To reduce the computational complexity of solving the orthogonal projection problem in the three-material model, we currently propose a new projection method for the three-material model that provides a very quick estimate of the three-material fractions without the use of code-book, which is pre-generated by uniformly sampling the model representation in material fraction space and used to find the best match with the observed measurements. In our new projection method for the three-material model, three pairs of two-material fractions are calculated by using the two-material model and then simply combined into a single triple of three-material fractions based on the barycentric interpolation in material fraction space. Experimental results using clinical datasets demonstrated that the proposed EC method showed higher cleansing quality and better preservation of submerged folds and polyps than the previous method. In addition, by using the new projection method for the three-material model, the proposed EC method clearly reconstructed the whole colon surface without the T-junction artifacts, which are observed as distracting ridges along the line where the air-TM interface touches the colon surface when the two-material model does not cope with the three-material fractions at T-junctions.Docto
Facilitating Colorectal Cancer Diagnosis with Computed Tomographic Colonography
Computed tomographic colonography (CTC) is a diagnostic technique involving helical volume acquisition of the cleansed, distended colorectum to detect colorectal cancer or potentially premalignant polyps. This Thesis summarises the evidence base, identifies areas in need of further research, quantifies sources of bias and presents novel techniques to facilitate colorectal cancer diagnosis using CTC. CTC literature is reviewed to justify the rationale for current implementation and to identify fruitful areas for research. This confirms excellent diagnostic performance can be attained providing CTC is interpreted by trained, experienced observers employing state-of-the-art implementation. The technique is superior to barium enema and consequently, it has been embraced by radiologists, clinicians and health policy-makers. Factors influencing generalisability of CTC research are investigated, firstly with a survey of European educational workshop participants which revealed limited CTC experience and training, followed by a systematic review exploring bias in research studies of diagnostic test accuracy which established that studies focussing on these aspects were lacking. Experiments to address these sources of bias are presented, using novel methodology: Conjoint analysis is used to ascertain patientsโ and cliniciansโ attitudes to false-positive screening diagnoses, showing that both groups overwhelmingly value sensitivity over specificity. The results inform a weighted statistical analysis for CAD which is applied to the results of two previous studies showing the incremental benefit is significantly higher for novices than experienced readers. We have employed eye-tracking technology to establish the visual search patterns of observers reading CTC, demonstrated feasibility and developed metrics for analysis. We also describe development and validation of computer software to register prone and supine endoluminal surface locations demonstrating accurate matching of corresponding points when applied to a phantom and a generalisable, publically available, CTC database. Finally, areas in need of future development are suggested
New Techniques in Gastrointestinal Endoscopy
As result of progress, endoscopy has became more complex, using more sophisticated devices and has claimed a special form. In this moment, the gastroenterologist performing endoscopy has to be an expert in macroscopic view of the lesions in the gut, with good skills for using standard endoscopes, with good experience in ultrasound (for performing endoscopic ultrasound), with pathology experience for confocal examination. It is compulsory to get experience and to have patience and attention for the follow-up of thousands of images transmitted during capsule endoscopy or to have knowledge in physics necessary for autofluorescence imaging endoscopy. Therefore, the idea of an endoscopist has changed. Examinations mentioned need a special formation, a superior level of instruction, accessible to those who have already gained enough experience in basic diagnostic endoscopy. This is the reason for what these new issues of endoscopy are presented in this book of New techniques in Gastrointestinal Endoscopy
Enhanced computer assisted detection of polyps in CT colonography
This thesis presents a novel technique for automatically detecting colorectal polyps in computed tomography colonography (CTC). The objective of the documented computer assisted diagnosis (CAD) technique is to deal with the issue of false positive detections without adversely affecting polyp detection sensitivity. The thesis begins with an overview of CTC and a review of the associated research areas, with particular attention given to CAD-CTC. This review identifies excessive false positive detections as a common problem associated with current CAD-CTC techniques. Addressing this problem constitutes the major contribution of this thesis. The documented CAD-CTC technique is trained with, and evaluated using, a series of clinical CTC data sets These data sets contain polyps with a range of different sizes and morphologies. The results presented m this thesis indicate the validity of the developed CAD-CTC technique and demonstrate its effectiveness m accurately detecting colorectal polyps while significantly reducing the number of false positive detections
Eye-tracking the moving medical image: Development and investigation of a novel investigational tool for CT Colonography
Colorectal cancer remains the third most common cancer in the UK but the second leading cause of cancer death with >16,000 dying per year. Many advances have been made in recent years in all areas of investigation for colorectal cancer, one of the more notable being the widespread introduction of CT Colonography (CTC). CTC has rapidly established itself as a cornerstone of diagnosis for colonic neoplasia and much work has been done to standardise and assure quality in practice in both the acquisition and interpretation of the technique. A novel feature of CTC is the presentation of imaging in both traditional 2D and the โvirtualโ 3D endoluminal formats. This thesis looks at expanding our understanding of and improving our performance in utilizing the endoluminal 3D view. We present and develop novel metrics applicable to eye-tracking the moving image, so that the complex dynamic nature of 3D endoluminal fly-through interpretation can be captured. These metrics are then applied to assess the effect of important elements of image interpretation, namely, reader experience, the effect of the use Computer Aided Detection (CAD) and the influence of the expected prevalence of abnormality. We review our findings with reference to the literature of eye tracking within medical imaging. In the co-registration section we apply our validated computer-assisted registration algorithm to the matching of 3D endoluminal colonic locations between temporally separate datasets, assessing its accuracy as an aid to colonic polyp surveillance with CTC
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Visualisation of curved tubular structures in medical databases: An application to virtual colonoscopy
Medical conditions affecting the colon are problematic to diagnose due to the difficulty in examining this particular internal organ. To date, the most widely used approach is to perform a colonoscopy; a procedure in which a small camera is inserted into the colon to examine its surface. This procedure is unpleasant and potentially dangerous for the patient, and is expensive and time consuming for the hospital. As a result, patients at risk of developing the conditions are not always screened as often as would be desirable.
Over the last few years a new approach known as virtual colonoscopy has been gaining popularity. The method uses information from a CT scan to reconstruct a 3D model of the colon which can then be examined without the patient needing to undergo a colonoscopy. This approach is now commonly used when screening for polyps (an indication of colon cancer) but can not be so easily used on conditions such as Inflammatory Bowel Disease (IBD) where information beyond the shape of the surface is required.
This thesis forms part of a larger project which aims to diagnose conditions such as IBD by using image processing algorithms on CT data and presenting the results to the user in an easy to interpret way. Specifically we are concerned with this visualisation stage of the system and so have developed a new visualisation approach which we call Volumetric CPR. This can be used to supplement the more traditional virtual flythrough visualisation and is applicable to IBD detection as well as screening for polyps.
Our technique builds on the concept of Curved Planar Reformation (CPR), which has proved to be a practical and widely used tool for the visualisation of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for structures such as the colon because abnormalities are smaller relative to the size of the structure and may not have such distinct density and shape characteristics.
Our new approach improves on this situation by using volume rendering for hollow regions of the structure and standard CPR, for the surrounding tissue. This effectively combines grey scale contextual information with detailed colour information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative for virtual colonoscopy.
We also demonstrate how systems can effectively utilize this new visualisation in order to convey maximum information to the user. We show how overlays can be used to present surface coverage data and how sophisticated lighting models can improve the users understanding of the 3D structure. We also present details of how to integrate our visualisation into existing systems and work flows
Registration of prone and supine CT colonography images and its clinical application
Computed tomographic (CT) colonography is a technique for detecting bowel cancer and potentially precancerous polyps. CT imaging is performed on the cleansed and insufflated bowel in order to produce a virtual endoluminal representation similar to optical colonoscopy. Because fluids and stool can mimic pathology, images are acquired with the patient in both prone and supine positions. Radiologists then match endoluminal locations visually between the two acquisitions in order to determine whether pathology is real or not. This process is hindered by the fact that the colon can undergo considerable deformation between acquisitions. Robust and accurate automated registration between prone and supine data acquisitions is therefore pivotal for medical interpretation, but a challenging problem. The method proposed in this thesis reduces the complexity of the registration task of aligning the prone and supine CT colonography acquisitions. This is done by utilising cylindrical representations of the colonic surface which reflect the colon's specific anatomy. Automated alignment in the cylindrical domain is achieved by non-rigid image registration using surface curvatures, applicable even when cases exhibit local luminal collapses. It is furthermore shown that landmark matches for initialisation improve the registration's accuracy and robustness. Additional performance improvements are achieved by symmetric and inverse-consistent registration and iteratively deforming the surface in order to compensate for differences in distension and bowel preparation. Manually identified reference points in human data and fiducial markers in a porcine phantom are used to validate the registration accuracy. The potential clinical impact of the method has been evaluated using data that reflects clinical practise. Furthermore, correspondence between follow-up CT colonography acquisitions is established in order to facilitate the clinical need to investigate polyp growth over time. Accurate registration has the potential to both improve the diagnostic process and decrease the radiologist's interpretation time. Furthermore, its result could be integrated into algorithms for improved computer-aided detection of colonic polyps
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