Stereo CT image compositing methods for lung nodule detection and characterization

On the performance of lung nodule detection, segmentation and classification

Computed tomography (CT) screening is an effective way for early detection of lung cancer in order to improve the survival rate of such a deadly disease. For more than two decades, image processing techniques such as nodule detection, segmentation, and classification have been extensively studied to assist physicians in identifying nodules from hundreds of CT slices to measure shapes and HU distributions of nodules automatically and to distinguish their malignancy. Thanks to new parallel computation, multi-layer convolution, nonlinear pooling operation, and the big data learning strategy, recent development of deep-learning algorithms has shown great progress in lung nodule screening and computer-assisted diagnosis (CADx) applications due to their high sensitivity and low false positive rates. This paper presents a survey of state-of-the-art deep-learning-based lung nodule screening and analysis techniques focusing on their performance and clinical applications, aiming to help better understand the current performance, the limitation, and the future trends of lung nodule analysis.

A mixed reality approach for stereo-tomographic quantification of lung nodules

To reduce the radiation dose and the equipment cost associated with lung CT screening, in this paper we propose a mixed reality based nodule measurement method with an active shutter stereo imaging system. Without involving hundreds of projection views and subsequent image reconstruction, we generated two projections of an iteratively placed ellipsoidal volume in the field of view and merging these synthetic projections with two original CT projections. We then demonstrated the feasibility of measuring the position and size of a nodule by observing whether projections of an ellipsoidal volume and the nodule are overlapped from a human observer's visual perception through the active shutter 3D vision glasses. The average errors of measured nodule parameters are less than 1 mm in the simulated experiment with 8 viewers. Hence, it could measure real nodules accurately in the experiments with physically measured projections.

A novel stereoscopic projection display system for CT images of fractures

The present study proposed a novel projection display system based on a virtual reality enhancement environment. The proposed system displays stereoscopic images of fractures and enhances the computed tomography (CT) images. The diagnosis and treatment of fractures primarily depend on the post-processing of CT images. However, two-dimensional (2D) images do not show overlapping structures in fractures since they are displayed without visual depth and these structures are too small to be simultaneously observed by a group of clinicians. Stereoscopic displays may solve this problem and allow clinicians to obtain more information from CT images. Hardware with which to generate stereoscopic images was designed. This system utilized the conventional equipment found in meeting rooms. The off-axis algorithm was adopted to convert the CT images into stereo image pairs, which were used as the input for a stereo generator. The final stereoscopic images were displayed using a projection system. Several CT fracture images were imported into the system for comparison with traditional 2D CT images. The results showed that the proposed system aids clinicians in group discussions by producing large stereoscopic images. The results demonstrated that the enhanced stereoscopic CT images generated by the system appear clearer and smoother, such that the sizes, displacement and shapes of bone fragments are easier to assess. Certain fractures that were previously not visible on 2D CT images due to vision overlap became vividly evident in the stereo images. The proposed projection display system efficiently, economically and accurately displayed three-dimensional (3D) CT images. The system may help clinicians improve the diagnosis and treatment of fractures.

Compare display schemes for lung nodule CT screening

This study investigated the relative efficiencies of a stereographic display and two monoscopic display schemes for detecting lung nodules in chest computed tomography (CT). The ultimate goal was to determine whether stereoscopic display provides advantages for visualization and interpretation of three-dimensional (3D) medical image datasets. A retrospective study that compared lung nodule detection performances achieved using three different schemes for displaying 3D CT data was conducted. The display modes included slice-by-slice, orthogonal maximum intensity projection (MIP), and stereoscopic display. One hundred lung-cancer screening CT examinations containing 647 nodules were interpreted by eight radiologists, in each of the display modes. Reading times and displayed slab thickness versus time were recorded, as well as the probability, location, and size for each detected nodule. Nodule detection performance was analyzed using the receiver operating characteristic method. The stereo display mode provided higher detection performance with a shorter interpretation time, as compared to the other display modes tested in the study, although the difference was not statistically significant. The analysis also showed that there was no difference in the patterns of displayed slab thickness versus time between the stereo and MIP display modes. Most radiologists preferred reading the 3D data at a slab thickness that corresponded to five CT slices. Our results indicate that stereo display has the potential to improve radiologists' performance for detecting lung nodules in CT datasets. The experience gained in conducting the study also strongly suggests that further benefits can be achieved through providing readers with additional functionality.

Real-time stereographic rendering and display of medical images with programmable GPUs

The study was to explore the power and feasibility of using programmable graphics processing units (GPUs) for real-time rendering and displaying large 3D medical datasets for stereoscopic display workstation. Lung cancer screening CT images were used for developing GPU-based stereo rendering and displaying. The study was run on a personal computer with a 128 MB NVIDIA Quadro FX 1100 graphics card. The performance of rendering and displaying was measured and compared between GPU-based and central processing unit (CPU)-based programming. The results indicate that GPU-based programming was capable of rendering large 3D datasets at real-time interactive rates with stereographic displays.

Characterization of radiologists' search strategies for lung nodule detection: slice-based versus volumetric displays

The goal of this study was to assess whether radiologists' search paths for lung nodule detection in chest computed tomography (CT) between different rendering and display schemes have reliable properties that can be exploited as an indicator of ergonomic efficiency for the purpose of comparing different display paradigms. Eight radiologists retrospectively viewed 30 lung cancer screening CT exams, containing a total of 91 nodules, in each of three display modes [i.e., slice-by-slice, orthogonal maximum intensity projection (MIP) and stereoscopic] for the purpose of detecting and classifying lung nodules. Radiologists' search patterns in the axial direction were recorded and analyzed along with the location, size, and shape for each detected feature, and the likelihood that the feature is an actual nodule. Nodule detection performance was analyzed by employing free-response receiver operating characteristic methods. Search paths were clearly different between slice-by-slice displays and volumetric displays but, aside from training and novelty effects, not between MIP and stereographic displays. Novelty and training effects were associated with the stereographic display mode, as evidenced by differences between the beginning and end of the study. The stereo display provided higher detection and classification performance with less interpretation time compared to other display modes tested in the study; however, the differences were not statistically significant. Our preliminary results indicate a potential role for the use of radiologists' search paths in evaluating the relative ergonomic efficiencies of different display paradigms, but systematic training and practice is necessary to eliminate training curve and novelty effects before search strategies can be meaningfully compared.