Fundamental Elements for Successful Performance of CT Colonography (Virtual Colonoscopy)

There are many factors affecting the successful performance of CT colonography (CTC). Adequate colonic cleansing and distention, the optimal CT technique and interpretation with using the newest CTC software by a trained reader will help ensure high accuracy for lesion detection. Fecal and fluid tagging may improve the diagnostic accuracy and allow for reduced bowel preparation. Automated carbon dioxide insufflation is more efficient and may be safer for colonic distention as compared to manual room air insufflation. CT scanning should use thin collimation of ≤3 mm with a reconstruction interval of ≤1.5 mm and a low radiation dose. There is not any one correct method for the interpretation of CTC; therefore, readers should be well-versed with both the primary 3D and 2D reviews. Polyps detected at CTC should be measured accurately and reported following the "polyp size-based" patient management system. The time-intensive nature of CTC and the limited resources for training radiologists appear to be the major barriers for implementing CTC in Korea

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

Computer-aided detection of polyps in CT colonography

Master'sMASTER OF ENGINEERIN

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

Multi-scale and multi-spectral shape analysis: from 2d to 3d

Shape analysis is a fundamental aspect of many problems in computer graphics and computer vision, including shape matching, shape registration, object recognition and classification. Since the SIFT achieves excellent matching results in 2D image domain, it inspires us to convert the 3D shape analysis to 2D image analysis using geometric maps. However, the major disadvantage of geometric maps is that it introduces inevitable, large distortions when mapping large, complex and topologically complicated surfaces to a canonical domain. It is demanded for the researchers to construct the scale space directly on the 3D shape. To address these research issues, in this dissertation, in order to find the multiscale processing for the 3D shape, we start with shape vector image diffusion framework using the geometric mapping. Subsequently, we investigate the shape spectrum field by introducing the implementation and application of Laplacian shape spectrum. In order to construct the scale space on 3D shape directly, we present a novel idea to solve the diffusion equation using the manifold harmonics in the spectral point of view. Not only confined on the mesh, by using the point-based manifold harmonics, we rigorously derive our solution from the diffusion equation which is the essential of the scale space processing on the manifold. Built upon the point-based manifold harmonics transform, we generalize the diffusion function directly on the point clouds to create the scale space. In virtue of the multiscale structure from the scale space, we can detect the feature points and construct the descriptor based on the local neighborhood. As a result, multiscale shape analysis directly on the 3D shape can be achieved