Automated planning of MRI scans of knee joints

Bystrov, Daniel; Pekar, Vladimir; Young, Stewart; Dries, Sebastian P. M.; Heese, Harald S.; Muiswinkel, Arianne M. C. van

doi:10.1117/12.709255

Cited by 16 publications

(11 citation statements)

References 5 publications

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“…Similar to earlier approaches (12,13), the scan geometry planning module was based on the previously generated training database: during the training period of the current study protocol, landmarks were extracted for each patient and each cardiac geometry and were rigidly registered into common reference frames. From these reference frames, atlas landmarks were calculated taking anatomic variability into account.…”

Section: Anatomy Recognition and Automated Cardiac Mr Geometry Planningmentioning

confidence: 99%

Fully automatic geometry planning for cardiac MR imaging and reproducibility of functional cardiac parameters

Frick¹,

Paetsch

Harder

et al. 2011

Magnetic Resonance Imaging

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Purpose: To establish operator-independent, fully automated planning of standard cardiac geometries and to determine the impact on interstudy reproducibility of cardiac functional parameters.Materials and Methods: Cardiac MR imaging was done in 50 patients referred for left-ventricular function assessment. In all patients, first standard manual planning was performed followed by automatic planning (AUTO1) and repeat automatic planning (AUTO2) after repositioning the patient to investigate interstudy reproducibility. Cardiac functional parameters were assessed and cine scans were visually graded on a 4-point scale from nondiagnostic to excellent.Results: Overall success rate of AUTO was 94% with good to excellent geometry planning in >94% of cine standard views. Comparing manual versus fully automated planning, a high agreement of cardiac functional parameters (Lin's concordance correlation coefficient, 0.91 to 0.99) with minimal percent bias (0.24 to 3.84%) was found. In addition, a high interstudy reproducibility of automatic planning was demonstrated (Lin's concordance correlation coefficient, 0.89 to 0.99; percent bias, 0.38 to 5.04%; precision, 3.46 to 9.09%). Conclusion:Fully automated planning of cardiac geometries could reliably be performed in patients showing a variety of cardiovascular pathologies. Standard cardiac geometries were precisely replicated and functional parameters were highly accurate.

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Section: Anatomy Recognition and Automated Cardiac Mr Geometry Planningmentioning

confidence: 99%

Fully automatic geometry planning for cardiac MR imaging and reproducibility of functional cardiac parameters

Frick¹,

Paetsch

Harder

et al. 2011

Magnetic Resonance Imaging

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“…The concept of computer-assisted scan planning was proposed before for human Magnetic Resonance Imaging of the heart [3][4], the brain [5], the knees [6] [7] or the spine [8]. These approaches are typically based on the registration of an a-priori model of the anatomy of interest to one or a set of scout views in 3D that are acquired before the high resolution scan.…”

Section: Methodsmentioning

confidence: 99%

Atlas-driven scan planning for high-resolution micro-SPECT data acquisition based on multi-view photographs: a pilot study

et al. 2009

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Highly focused Micro-SPECT scanners enable the acquisition of functional small animal data with very high-resolution. To acquire a maximum of emitted photons from a specific structure of interest and at the same time minimize the required acquisition time, typically only a small subvolume of the animal is scanned that contains the organs of interest. This Volume of Interest (VOI) can be defined manually based on photographs of the animal taken prior to SPECT scanning, for example two lateral views and a top view. In these photographs however, only the surface of the animal is visible and therefore visual estimation of the location of these organs may be difficult.In this paper, we propose a novel atlas-based technique for estimating the organ VOI for the major organs by mapping a small animal atlas to optical scout images. The user is required to outline the animal contour in one lateral view, and to mark two lateral landmarks in the top view photograph. These landmarks subsequently serve as fiducial landmarks to define a 3D Thin-Plate-Spline mapping of an anatomical mouse atlas to the photographic coordinate space. Planar projections of the mapped atlas organs on the photographs greatly facilitate the estimation of the size and position of the target organ. To validate the proposed approach, the estimated organ VOIs were compared to manually drawn organ outlines in a Micro-CT scan, which was co-registered to the scout photographs using physical landmarks. The results demonstrate a highly promising volume correspondence between the real and the estimated organ VOIs.

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“…Analogously to previous work [2,5], the method uses a training set of manually planned geometries to propose a planning based on correlation with the automatically detected anatomical landmarks. On the training samples, rigid registration of the automatically detected landmarks is carried out.…”

Section: Scan Geometry Planningmentioning

confidence: 99%

“…Analogously to earlier work [2,5], the detected anatomical landmarks are used to learn pre-defined geometries from a training set provided by the operator. In this way, the ASP system allows to consistently plan scan geometries tailored to individual needs and preferences of the radiologist.…”

Section: Introductionmentioning

confidence: 99%

Automated Planning of Scan Geometries in Spine MRI Scans

Pekar

Bystrov

Heese

et al. 2007

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

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Abstract. 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.

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Automated planning of MRI scans of knee joints

Cited by 16 publications

References 5 publications

Fully automatic geometry planning for cardiac MR imaging and reproducibility of functional cardiac parameters

Fully automatic geometry planning for cardiac MR imaging and reproducibility of functional cardiac parameters

Atlas-driven scan planning for high-resolution micro-SPECT data acquisition based on multi-view photographs: a pilot study

Automated Planning of Scan Geometries in Spine MRI Scans

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