Registration of the endoluminal surfaces of the colon derived from prone and supine CT colonography

Purpose: Computed tomographic (CT) colonography is a relatively new technique for detecting bowel cancer or potentially precancerous polyps. CT scanning is combined with three-dimensional (3D) image reconstruction to produce a virtual endoluminal representation similar to optical colonoscopy. Because retained fluid and stool can mimic pathology, CT data are acquired with the bowel cleansed and insufflated with gas and patient in both prone and supine positions. Radiologists then match visually endoluminal locations between the two acquisitions in order to determine whether apparent pathology is real or not. This process is hindered by the fact that the colon, essentially a long tube, can undergo considerable deformation between acquisitions. The authors present a novel approach to automatically establish spatial correspondence between prone and supine endoluminal colonic surfaces after surface parameterization, even in the case of local colon collapse.Methods: The complexity of the registration task was reduced from a 3D to a 2D problem by mapping the surfaces extracted from prone and supine CT colonography onto a cylindrical parameterization. A nonrigid cylindrical registration was then performed to align the full colonic surfaces. The curvature information from the original 3D surfaces was used to determine correspondence. The method can also be applied to cases with regions of local colonic collapse by ignoring the collapsed regions during the registration.Results: Using a development set, suitable parameters were found to constrain the cylindrical registration method. Then, the same registration parameters were applied to a different set of 13 validation cases, consisting of 8 fully distended cases and 5 cases exhibiting multiple colonic collapses. All polyps present were well aligned, with a mean (+/- std. dev.) registration error of 5.7 (+/- 3.4) mm. An additional set of 1175 reference points on haustral folds spread over the full endoluminal colon surfaces resulted in an error of 7.7 (+/- 7.4) mm. Here, 82% of folds were aligned correctly after registration with a further 15% misregistered by just onefold.Conclusions: The proposed method reduces the 3D registration task to a cylindrical registration representing the endoluminal surface of the colon. Our algorithm uses surface curvature information as a similarity measure to drive registration to compensate for the large colorectal deformations that occur between prone and supine data acquisitions. The method has the potential to both enhance polyp detection and decrease the radiologist's interpretation time. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3577603

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

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

A fully automatic CAD-CTC system based on curvature analysis for standard and low-dose CT data

Computed tomography colonography (CTC) is a rapidly evolving noninvasive medical investigation that is viewed by radiologists as a potential screening technique for the detection of colorectal polyps. Due to the technical advances in CT system design, the volume of data required to be processed by radiologists has increased significantly, and as a consequence the manual analysis of this information has become an increasingly time consuming process whose results can be affected by inter- and intrauser variability. The aim of this paper is to detail the implementation of a fully integrated CAD-CTC system that is able to robustly identify the clinically significant polyps in the CT data. The CAD-CTC system described in this paper is a multistage implementation whose main system components are: 1) automatic colon segmentation; 2) candidate surface extraction; 3) feature extraction; and 4) classification. Our CAD-CTC system performs at 100% sensitivity for polyps larger than 10 mm, 92% sensitivity for polyps in the range 5 to 10 mm, and 57.14% sensitivity for polyps smaller than 5 mm with an average of 3.38 false positives per dataset. The developed system has been evaluated on synthetic and real patient CT data acquired with standard and low-dose radiation levels

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

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 patients‘ and clinicians’ 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

물질 혼합비율과 구조적 특징의 통합 재구성 모델을 이용한 전자적 장세척 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 8. 신영길.대장 컴퓨터 단층 촬영 영상에서 조영 처리된 잔여물을 제거하기 위해 전자적 장세척 방법이 이용된다. 본 논문에서는 전자적 장세척 방법에서 결함의 주요 원인이 되는 부분 용적 효과와 가성 상승 효과를 동시에 해결하기 위해 물질 혼합비율과 구조적 특징의 통합 재구성 모델을 이용한 전자적 장청소 기법을 제안한다. 먼저 대장 컴퓨터 단층 촬영 영상에서 공기, 조영 처리된 잔여물, 공기와 조영 처리된 잔여물 사이의 경계 (공기-잔여물 경계), 대장외부의 연조직과 조영 처리된 잔여물 사이의 경계 (연조직-잔여물 경계), 그리고 공기, 연조직, 조영 처리된 잔여물이 만나는 경계 (공기-연조직-잔여물 경계) 영역을 포함한 결장 요소를 분할한다. 분할된 공기와 공기-잔여물 경계 영역에 대해서는 각 복셀의 밀도값을 동일하게 공기의 대표 밀도값으로 대체함으로써 잔여물을 제거한다. 반면에 분할된 연조직-잔여물 경계와 공기-연조직-잔여물 경계 영역에 대해서는 물질 혼합비율과 구조적 특징을 계산한다. 물질 혼합비율은 두 물질간 혹은 세 물질간 전이 모델을 이용하여 예측하고 구조적 특징은 헤시안 행렬의 아이겐 분석에 기반하여 계산한다. 계산된 물질 혼합비율과 구조적 특징을 이용하여 연조직-잔여물 경계와 공기-연조직-잔여물 경계 영역에 속하는 각 복셀의 밀도값이 재구성된다. 물질 혼합비율과 구조적 특징의 통합 재구성 모델은 각 복셀 내의 연조직의 부분 용적을 유지시키는 동시에 조영 처리된 잔여물의 가성 상승 효과로 인해 약화된 잔여물에 잠긴 대장 주름 및 용종이 보존될 수 있도록 한다. 따라서 제안된 전자적 장세척 방법에서는 부분 용적 효과로 인한 연조직-잔여물 경계의 계단무늬 결함과 가성 상승 효과로 인한 잔여물에 잠긴 대장 주름 및 용종의 지나친 세척 결함을 피할 수 있다. 또한 본 논문에서는 기존 세 물질간 전이 모델의 연산 복잡도를 줄이기 위해 단순 세 물질간 전이 모델을 제안한다. 단순 세 물질간 전이 모델에서는 두 물질간 전이 모델을 반복 적용시킴으로써 얻어진 세 쌍의 (공기-연조직, 공기-잔여물, 연조직-잔여물) 두 물질간 혼합비율을 구하고 이를 삼각형을 이용한 무게중심좌표 상에서의 보간방법을 이용해 하나의 세 물질간 혼합비율로 변환한다. 열개의 임상 데이터를 이용하여 제안한 전자적 장세척 방법의 성능을 평가하였다. 방사선 전문의에 의한 장세척 품질 평가에서 제안 방법이 물질 혼합비율을 이용한 기존 방법에 비해 더 높은 점수의 장세척 결과를 보였으며, 특히 잔여물에 잠긴 대장 주름 및 용종이 더 잘 보존되는 것을 확인하였다. 이러한 결과는 잔여물에 잠긴 대장 주름 영역을 수동 분할하여 제안 방법과 기존 방법에 의한 장세척 결과 영상에서 해당 영역의 평균 밀도값과 주름 보존 비율을 비교한 결과에서도 마찬가지로 입증되었다. 또한 기존의 두 물질간 전이 모델로는 잘 해결되지 않았던 공기-연조직-잔여물 경계 영역에서의 산등성이 형태의 결함에 대해서도 제안 방법에서는 단순 세 물질간 전이 모델을 이용하여 공기-연조직-잔여물 경계 영역에서의 결함을 제거하고 전체 대장의 표면이 깨끗하게 재구성되는 것을 확인하였다.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

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