Automated Planning of Scan Geometries in Spine MRI Scans Pekar, Vladimir; Bystrov, Daniel; Heese, Harald S. ...
Lecture Notes in Computer Science,
2007, Letnik:
10, Številka:
Pt 1
Book Chapter, Journal Article, Conference Proceeding
Recenzirano
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Consistency of MR scan planning is very important for diagnosis, especially in multi-site trials and follow-up studies, where disease progress or response to treatment is evaluated. Accurate manual ...scan planning is tedious and requires skillful operators. On the other hand, automated scan planning is difficult due to relatively low quality of survey images (“scouts”) and strict processing time constraints. This paper presents a novel method for automated planning of MRI scans of the spine. Lumbar and cervical examinations are considered, although the proposed method is extendible to other types of spine examinations, such as thoracic or total spine imaging. The automated scan planning (ASP) system consists of an anatomy recognition part, which is able to automatically detect and label the spine anatomy in the scout scan, and a planning part, which performs scan geometry planning based on recognized anatomical landmarks. A validation study demonstrates the robustness of the proposed method and its feasibility for clinical use.
Abstract Background and Aim Issues in patient positioning during chest X-ray (CXR) acquisition impair diagnostic quality and potentially increase radiation dose. Automated quality assessment was ...proposed to address this. Our objective is to determine thresholds on some quality control metrics following international guidelines, that represent expert knowledge and can be applied in a comprehensible and explainable AI approach for such an automatic quality assessment. Materials and Methods An AI-method estimating collimation distance to the ribcage, balancing between both clavicle heads, and number of ribs above the diaphragm as metrics for collimation, rotation, and inhalation quality was applied on 64,315 posteroanterior CXR images from a public dataset (ChestX-ray8). From this set 920 CXR images were sampled and manually annotated to gain additional trusted reference metrics. Seven readers from different institutions then classified the acquisition quality of these images independently into okay, inadequate, or unacceptable following the criteria of international guidelines. Optimal thresholds on the metrics were determined to reproduce these classes using the metrics only. Results A fair to moderate agreement between the experts was found. When disregarding all inadequate rates a classification on the metrics was able to separate okay rated cases from unacceptable cases for collimation (AUC 0.97), rotation (AUC = 0.93) and inhalation (AUC = 0.97). Conclusion Suitable thresholds were determined to reproduce expert opinions in the assessment of the most important quality criteria in CXR acquisition. These thresholds were finally applied on the AI-method's estimates to automatically classify image acquisition quality comprehensibly and according to the guidelines.
The detection and extraction of complex anatomical structures usually involves a trade-off between the complexity of local feature extraction and classification, and the complexity and performance of ...the subsequent structural inference from the viewpoint of combinatorial optimization. Concerning the latter, computationally efficient methods are of particular interest that return the globally-optimal structure.
We present an efficient method for part-based localization of anatomical structures which embeds contextual shape knowledge in a probabilistic graphical model. It allows for robust detection even when some of the part detections are missing. The application scenario for our statistical evaluation is spine detection and labeling in magnetic resonance images.
Robust initialization is essential for any successful segmentation process of medical images. For CT images, initialization is challenging because quality, appearance, content, and field-of-view of ...the images are highly variable. Furthermore, high execution speed is desirable, whereas the user tolerance to errors is low in clinical applications. We present a new method for efficient and robust positioning of organs in CT images. It is based on a novel probabilistic atlas that, given a tissue type, describes the probability density of the random variable spatial location. Random sampling is then employed to select the most informative points for matching. We present results on pelvic and abdominal images acquired for radiotherapy planning.
The detection and extraction of complex anatomical structures usually involves a trade-off between the complexity of local feature extraction and classification, and the complexity and performance of ...the subsequent structural inference from the viewpoint of combinatorial optimization. Concerning the latter, computationally efficient methods are of particular interest that return the globally-optimal structure. We present an efficient method for part-based localization of anatomical structures which embeds contextual shape knowledge in a probabilistic graphical model. It allows for robust detection even when some of the part detections are missing. The application scenario for our statistical evaluation is spine detection and labeling in magnetic resonance images.
Assessment of soft tissue in normal and abnormal joint motion today gets feasible by acquiring time series of 3D MRI images. However, slice-by-slice viewing of such 4D kinematic images is cumbersome, ...and does not allow appreciating the movement in a convenient way. Simply presenting slice data in a cine-loop will be compromised by through-plane displacements of anatomy and “jerks” between frames, both of which hamper visual analysis of the movement. To overcome these limitations, we have implemented a demonstrator for viewing 4D kinematic MRI datasets. It allows to view any user defined anatomical structure from any viewing perspective in real-time. Smoothly displaying the movement in a cine-loop is realized by image post processing, fixing any user defined anatomical structure after image acquisition.
The acquisition of time series of 3D MR images is becoming feasible nowadays, which enables the assessment of bone and soft tissue in normal and abnormal joint motion. Fast two-dimensional (2D) ...scanning of moving joints may also provide high temporal resolution but is limited to a single, predefined slice. Acquiring 3D time series has the advantage that after the acquisition image processing and visualization techniques can be used to reformat the images to any orientation and to reduce the through-plane motion and undesired gross motion superimposed on the relevant joint movement. In this publication, we first review such post-processing techniques for retrospective tracking of viewing planes according to a single moving rigid body (e.g. bone). Then, we present new numerical schemes for optimally tracking viewing planes according to the movement of multiple structures to compensate for their through- as well as in-plane motion. These structures can be specified in an interactive viewing program, and the motion compensated movies can be updated and displayed in real-time. The post-processing algorithms require a 4D motion-field estimation which also can be utilized to interpolate intermediate images to present the final movies in smooth cine-loops and to significantly improve the visual perceptibility of complex joint movement.
MRI is capable of acquiring time series of 3D images, which gives a 4D examination that can be used for kinematic joint imaging of an unrestricted movement. However, slice-by-slice viewing of the 4D ...images is cumbersome, and does not allow to appreciate the movement. Simply presenting slice data in a cine loop will be compromised by through-plane displacements of anatomy and “jerks” between frames, both of which hamper visual analysis of the movement. To overcome these limitations, we have implemented a prototype for viewing 4D kinematic MRI data sets. It allows to view in real-time any user defined anatomical structure from any viewing perspective. Smoothly displaying the movement in a cine loop is realized by image post-processing, fixing any user defined anatomical structures after image acquisition.
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