6 research outputs found

    Feature extraction to aid disease detection and assessment of disease progression in CT and MR colonography

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    Computed tomographic colonography (CTC) is a technique employed to examine the whole colon for cancers and premalignant adenomas (polyps). Oral preparation is taken to fully cleanse the colon, and gas insufflation maximises the attenuation contrast between the enoluminal colon surface and the lumen. The procedure is performed routinely with the patient both prone and supine to redistribute gas and residue. This helps to differentiate fixed colonic pathology from mobile faecal residue and also helps discover pathology occluded by retained fluid or luminal collapse. Matching corresponding endoluminal surface locations with the patient in the prone and supine positions is therefore an essential aspect of interpretation by radiologists; however, interpretation can be difficult and time consuming due to the considerable colonic deformations that occur during repositioning. Hence, a method for automated registration has the potential to improve efficiency and diagnostic accuracy. I propose a novel method to establish correspondence between prone and supine CT colonography acquisitions automatically. The problem is first simplified by detecting haustral folds which are elongated ridgelike endoluminal structures and can be identified by curvature based measurements. These are subsequently matched using appearance based features, and their relative geometric relationships. It is shown that these matches can be used to find correspondence along the full length of the colon, but may also be used in conjunction with other registration methods to achieve a more robust and accurate result, explicitly addressing the problem of colonic collapse. The potential clinical value of this method has been assessed in an external clinical validation, and the application to follow-up CTC surveillance has been investigated. MRI has recently been applied as a tool to quantitatively evaluate the therapeutic response to therapy in patients with Crohn's disease, and is the preferred choice for repeated imaging. A primary biomarker for this evaluation is the measurement of variations of bowel wall thickness on changing from the active phase of the disease to remission; however, a poor level of interobserver agreement of measured thickness is reported and therefore a system for accurate, robust and reproducible measurements is desirable. I propose a novel method which will automatically track sections of colon, by estimating the positions of elliptical cross sections. Subsequently, estimation of the positions of the inner and outer bowel walls are made based on image gradient information and therefore a thickness measurement value can be extracted

    Facilitating Colorectal Cancer Diagnosis with Computed Tomographic Colonography

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    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

    External Clinical Validation of Prone and Supine CT Colonography Registration

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    This paper provides an external validation of a prone-supine registration algorithm for CT colonography (CTC). A validation sample of 49 patient cases with 66 polyps (6 to 30 mm) was selected from a publicly available, anonymized CTC archive. To enhance generalizability, no case was excluded due to poor preparation or inadequate distension. Corresponding prone and supine polyp coordinates were recorded and the endoluminal surfaces registered: a Markov Random Field technique was used to find feature matches between prone/supine acquisitions and following mapping of the endoluminal surface to a cylinder, dense surface correspondence was achieved via cylindrical non-rigid registration. The polyp registration error was determined and a subjective assessment of registration made for 2D slice-based and 3D endoluminal data display using a pre-specified scoring system. Results were compared to using โ€œnormalized distance along the colon centerlineโ€ (NDACC) which approximates to the method currently employed to match colonic positions using proprietary CT colonography interpretation software. Registration was possible in all 49 cases. Overall mean 3D polyp registration error was significantly smaller with 19.9 mm in comparison to 27.7 mm using NDACC (p=0.001). 82.7% of polyp matches were defined as โ€œsuccessfulโ€ in comparison to 37.1% using NDACC according to the pre-specified criteria. Similarly, using 2D visualization, 62.1% registrations were โ€œsuccessfulโ€ and only 22.7% using NDACC. Full surface-based prone-to-supine registration can successfully map the location of a polyp identified on one acquisition to the corresponding endoluminal surface in the opposing acquisition, greatly facilitating polyp matching and aiding interpretation. Our method compares favorably to using NDACC

    ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ๊ณผ ๊ตฌ์กฐ์  ํŠน์ง•์˜ ํ†ตํ•ฉ ์žฌ๊ตฌ์„ฑ ๋ชจ๋ธ์„ ์ด์šฉํ•œ ์ „์ž์  ์žฅ์„ธ์ฒ™ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2013. 8. ์‹ ์˜๊ธธ.๋Œ€์žฅ ์ปดํ“จํ„ฐ ๋‹จ์ธต ์ดฌ์˜ ์˜์ƒ์—์„œ ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ์„ ์ œ๊ฑฐํ•˜๊ธฐ ์œ„ํ•ด ์ „์ž์  ์žฅ์„ธ์ฒ™ ๋ฐฉ๋ฒ•์ด ์ด์šฉ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ „์ž์  ์žฅ์„ธ์ฒ™ ๋ฐฉ๋ฒ•์—์„œ ๊ฒฐํ•จ์˜ ์ฃผ์š” ์›์ธ์ด ๋˜๋Š” ๋ถ€๋ถ„ ์šฉ์  ํšจ๊ณผ์™€ ๊ฐ€์„ฑ ์ƒ์Šน ํšจ๊ณผ๋ฅผ ๋™์‹œ์— ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ๊ณผ ๊ตฌ์กฐ์  ํŠน์ง•์˜ ํ†ตํ•ฉ ์žฌ๊ตฌ์„ฑ ๋ชจ๋ธ์„ ์ด์šฉํ•œ ์ „์ž์  ์žฅ์ฒญ์†Œ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ € ๋Œ€์žฅ ์ปดํ“จํ„ฐ ๋‹จ์ธต ์ดฌ์˜ ์˜์ƒ์—์„œ ๊ณต๊ธฐ, ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ, ๊ณต๊ธฐ์™€ ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ ์‚ฌ์ด์˜ ๊ฒฝ๊ณ„ (๊ณต๊ธฐ-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„), ๋Œ€์žฅ์™ธ๋ถ€์˜ ์—ฐ์กฐ์ง๊ณผ ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ ์‚ฌ์ด์˜ ๊ฒฝ๊ณ„ (์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„), ๊ทธ๋ฆฌ๊ณ  ๊ณต๊ธฐ, ์—ฐ์กฐ์ง, ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ์ด ๋งŒ๋‚˜๋Š” ๊ฒฝ๊ณ„ (๊ณต๊ธฐ-์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„) ์˜์—ญ์„ ํฌํ•จํ•œ ๊ฒฐ์žฅ ์š”์†Œ๋ฅผ ๋ถ„ํ• ํ•œ๋‹ค. ๋ถ„ํ• ๋œ ๊ณต๊ธฐ์™€ ๊ณต๊ธฐ-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„ ์˜์—ญ์— ๋Œ€ํ•ด์„œ๋Š” ๊ฐ ๋ณต์…€์˜ ๋ฐ€๋„๊ฐ’์„ ๋™์ผํ•˜๊ฒŒ ๊ณต๊ธฐ์˜ ๋Œ€ํ‘œ ๋ฐ€๋„๊ฐ’์œผ๋กœ ๋Œ€์ฒดํ•จ์œผ๋กœ์จ ์ž”์—ฌ๋ฌผ์„ ์ œ๊ฑฐํ•œ๋‹ค. ๋ฐ˜๋ฉด์— ๋ถ„ํ• ๋œ ์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„์™€ ๊ณต๊ธฐ-์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„ ์˜์—ญ์— ๋Œ€ํ•ด์„œ๋Š” ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ๊ณผ ๊ตฌ์กฐ์  ํŠน์ง•์„ ๊ณ„์‚ฐํ•œ๋‹ค. ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ์€ ๋‘ ๋ฌผ์งˆ๊ฐ„ ํ˜น์€ ์„ธ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์„ ์ด์šฉํ•˜์—ฌ ์˜ˆ์ธกํ•˜๊ณ  ๊ตฌ์กฐ์  ํŠน์ง•์€ ํ—ค์‹œ์•ˆ ํ–‰๋ ฌ์˜ ์•„์ด๊ฒ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๊ณ„์‚ฐํ•œ๋‹ค. ๊ณ„์‚ฐ๋œ ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ๊ณผ ๊ตฌ์กฐ์  ํŠน์ง•์„ ์ด์šฉํ•˜์—ฌ ์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„์™€ ๊ณต๊ธฐ-์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„ ์˜์—ญ์— ์†ํ•˜๋Š” ๊ฐ ๋ณต์…€์˜ ๋ฐ€๋„๊ฐ’์ด ์žฌ๊ตฌ์„ฑ๋œ๋‹ค. ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ๊ณผ ๊ตฌ์กฐ์  ํŠน์ง•์˜ ํ†ตํ•ฉ ์žฌ๊ตฌ์„ฑ ๋ชจ๋ธ์€ ๊ฐ ๋ณต์…€ ๋‚ด์˜ ์—ฐ์กฐ์ง์˜ ๋ถ€๋ถ„ ์šฉ์ ์„ ์œ ์ง€์‹œํ‚ค๋Š” ๋™์‹œ์— ์กฐ์˜ ์ฒ˜๋ฆฌ๋œ ์ž”์—ฌ๋ฌผ์˜ ๊ฐ€์„ฑ ์ƒ์Šน ํšจ๊ณผ๋กœ ์ธํ•ด ์•ฝํ™”๋œ ์ž”์—ฌ๋ฌผ์— ์ž ๊ธด ๋Œ€์žฅ ์ฃผ๋ฆ„ ๋ฐ ์šฉ์ข…์ด ๋ณด์กด๋  ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ œ์•ˆ๋œ ์ „์ž์  ์žฅ์„ธ์ฒ™ ๋ฐฉ๋ฒ•์—์„œ๋Š” ๋ถ€๋ถ„ ์šฉ์  ํšจ๊ณผ๋กœ ์ธํ•œ ์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„์˜ ๊ณ„๋‹จ๋ฌด๋Šฌ ๊ฒฐํ•จ๊ณผ ๊ฐ€์„ฑ ์ƒ์Šน ํšจ๊ณผ๋กœ ์ธํ•œ ์ž”์—ฌ๋ฌผ์— ์ž ๊ธด ๋Œ€์žฅ ์ฃผ๋ฆ„ ๋ฐ ์šฉ์ข…์˜ ์ง€๋‚˜์นœ ์„ธ์ฒ™ ๊ฒฐํ•จ์„ ํ”ผํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ธฐ์กด ์„ธ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์˜ ์—ฐ์‚ฐ ๋ณต์žก๋„๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด ๋‹จ์ˆœ ์„ธ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹จ์ˆœ ์„ธ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์—์„œ๋Š” ๋‘ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์„ ๋ฐ˜๋ณต ์ ์šฉ์‹œํ‚ด์œผ๋กœ์จ ์–ป์–ด์ง„ ์„ธ ์Œ์˜ (๊ณต๊ธฐ-์—ฐ์กฐ์ง, ๊ณต๊ธฐ-์ž”์—ฌ๋ฌผ, ์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ) ๋‘ ๋ฌผ์งˆ๊ฐ„ ํ˜ผํ•ฉ๋น„์œจ์„ ๊ตฌํ•˜๊ณ  ์ด๋ฅผ ์‚ผ๊ฐํ˜•์„ ์ด์šฉํ•œ ๋ฌด๊ฒŒ์ค‘์‹ฌ์ขŒํ‘œ ์ƒ์—์„œ์˜ ๋ณด๊ฐ„๋ฐฉ๋ฒ•์„ ์ด์šฉํ•ด ํ•˜๋‚˜์˜ ์„ธ ๋ฌผ์งˆ๊ฐ„ ํ˜ผํ•ฉ๋น„์œจ๋กœ ๋ณ€ํ™˜ํ•œ๋‹ค. ์—ด๊ฐœ์˜ ์ž„์ƒ ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ œ์•ˆํ•œ ์ „์ž์  ์žฅ์„ธ์ฒ™ ๋ฐฉ๋ฒ•์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋ฐฉ์‚ฌ์„  ์ „๋ฌธ์˜์— ์˜ํ•œ ์žฅ์„ธ์ฒ™ ํ’ˆ์งˆ ํ‰๊ฐ€์—์„œ ์ œ์•ˆ ๋ฐฉ๋ฒ•์ด ๋ฌผ์งˆ ํ˜ผํ•ฉ๋น„์œจ์„ ์ด์šฉํ•œ ๊ธฐ์กด ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ๋” ๋†’์€ ์ ์ˆ˜์˜ ์žฅ์„ธ์ฒ™ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€์œผ๋ฉฐ, ํŠนํžˆ ์ž”์—ฌ๋ฌผ์— ์ž ๊ธด ๋Œ€์žฅ ์ฃผ๋ฆ„ ๋ฐ ์šฉ์ข…์ด ๋” ์ž˜ ๋ณด์กด๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ž”์—ฌ๋ฌผ์— ์ž ๊ธด ๋Œ€์žฅ ์ฃผ๋ฆ„ ์˜์—ญ์„ ์ˆ˜๋™ ๋ถ„ํ• ํ•˜์—ฌ ์ œ์•ˆ ๋ฐฉ๋ฒ•๊ณผ ๊ธฐ์กด ๋ฐฉ๋ฒ•์— ์˜ํ•œ ์žฅ์„ธ์ฒ™ ๊ฒฐ๊ณผ ์˜์ƒ์—์„œ ํ•ด๋‹น ์˜์—ญ์˜ ํ‰๊ท  ๋ฐ€๋„๊ฐ’๊ณผ ์ฃผ๋ฆ„ ๋ณด์กด ๋น„์œจ์„ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ์—์„œ๋„ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์ž…์ฆ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ๊ธฐ์กด์˜ ๋‘ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ๋กœ๋Š” ์ž˜ ํ•ด๊ฒฐ๋˜์ง€ ์•Š์•˜๋˜ ๊ณต๊ธฐ-์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„ ์˜์—ญ์—์„œ์˜ ์‚ฐ๋“ฑ์„ฑ์ด ํ˜•ํƒœ์˜ ๊ฒฐํ•จ์— ๋Œ€ํ•ด์„œ๋„ ์ œ์•ˆ ๋ฐฉ๋ฒ•์—์„œ๋Š” ๋‹จ์ˆœ ์„ธ ๋ฌผ์งˆ๊ฐ„ ์ „์ด ๋ชจ๋ธ์„ ์ด์šฉํ•˜์—ฌ ๊ณต๊ธฐ-์—ฐ์กฐ์ง-์ž”์—ฌ๋ฌผ ๊ฒฝ๊ณ„ ์˜์—ญ์—์„œ์˜ ๊ฒฐํ•จ์„ ์ œ๊ฑฐํ•˜๊ณ  ์ „์ฒด ๋Œ€์žฅ์˜ ํ‘œ๋ฉด์ด ๊นจ๋—ํ•˜๊ฒŒ ์žฌ๊ตฌ์„ฑ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.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
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