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Nashua, NH, United States

iCAD Inc. , headquartered in Nashua, New Hampshire, is a medical-device manufacturer. Having acquired another device-maker, Xoft, at the end of 2010, iCAD almost immediately faced a case of mistaken consequences in some Xoft test-study patients. Wikipedia.

Verma S.,University of Cincinnati | Turkbey B.,U.S. National Institutes of Health | Muradyan N.,iCAD | Rajesh A.,University of Leicester | And 3 more authors.
American Journal of Roentgenology | Year: 2012

OBJECTIVE. This article is a primer on the technical aspects of performing a high-quality dynamic contrast-enhanced MRI (DCE-MRI) examination of the prostate gland. CONCLUSION. DCE-MRI is emerging as a useful clinical technique as part of a multi-parametric approach for evaluating the extent of primary and recurrent prostate cancer. Performing a high-quality DCE-MRI examination requires a good understanding of the technical aspects and limitations of image acquisition and postprocessing techniques. © American Roentgen Ray Society. Source

Delongchamps N.B.,Assistance Publique Hopitaux de Paris | Peyromaure M.,Assistance Publique Hopitaux de Paris | Schull A.,Assistance Publique Hopitaux de Paris | Beuvon F.,Assistance Publique Hopitaux de Paris | And 7 more authors.
Journal of Urology | Year: 2013

Purpose: We compared the accuracy of visual targeted biopsies vs computerized transrectal ultrasound-magnetic resonance imaging registration using a rigid (Esaote®, nondeformable) or elastic (Koelis®, deformable) approach. Materials and Methods: A total of 391 consecutive patients with suspected localized prostate cancer were prospectively included in analysis. All patients underwent prostate magnetic resonance imaging, followed by 10 to 12-core random prostate biopsies. When magnetic resonance imaging detected suspicious findings, targeted biopsy was performed, including visual, rigid system and elastic system targeted biopsies in the first 127 patients, the next 131 and the last 133, respectively. Cancer detection rates were assessed by conditional logistic regression. Targeted biopsies alone and random biopsies were further compared for the amount of tissue sampled and microfocal cancer detection, the latter defined as a single core with 5 mm or less of Gleason 6 cancer. Results: Patient characteristics and random biopsy detection rates were similar among the groups. Magnetic resonance imaging detected at least 1 suspicious area in 54 (42%), 78 (59%) and 82 patients (62%) in groups 1, 2 and 3, respectively. The cancer detection rates of rigid and elastic system targeted biopsies were significantly higher than the random biopsy rate (p = 0.0065 and 0.0016, respectively). Visual targeted biopsy did not perform better than random biopsy (p = 0.66). Rigid and elastic system targeted biopsies allowed for decreasing the number of cores and the detection of microfocal cancer, while increasing the detection of high grade cancer. Conclusions: When performed with computerized magnetic resonance imaging-transrectal ultrasound image registration, targeted biopsy alone improved cancer detection over random biopsies, decreased the detection rate of microfocal cancer and increased the detection rate of cancer with a Gleason score of greater than 6. © 2013 American Urological Association Education and Research, Inc. Source

A system and a method are disclosed that forms a novel, synthetic, two-dimensional image of an anatomical region such as a breast. Two-dimensional regions of interest (ROIs) such as masses are extracted from three-dimensional medical image data, such as digital tomosynthesis reconstructed volumes. Using image processing technologies, the ROIs are then blended with two-dimensional image information of the anatomical region to form the synthetic, two-dimensional image. This arrangement and resulting image desirably improves the workflow of a physician reading medical image data, as the synthetic, two-dimensional image provides detail previously only seen by interrogating the three-dimensional medical image data.

Disclosed are methods, and associated systems comprising processors, input devices and output devices, of detecting regions of interest in a tomographic breast image. The methods may comprise: acquiring tomographic breast image data; deriving a plurality of synthetic sub-volumes from the tomographic breast image data; wherein each subvolume is defined by parallel planar top and bottom surfaces; wherein planar top and bottom surfaces of successive subvolumes are parallel to each other; and wherein a top planar surface of a sub-volume is offset from a top planar surface of a prior sub-volume, such that successive sub-volumes overlap; for each sub-volume, deriving a two-dimensional image; for each two-dimensional image, identifying regions of interest therein; deriving at least one region of interest of potential clinical interest from a plurality of identified regions of interest; and outputting information associated with at least one derived region of interest of potential clinical interest.

This discloses methods and systems for the processing of medical image data of a colon acquired with an imaging device, such as a computerized tomography (CT) scanner and more particularly, to methods and systems for the classification of structures or objects in said medical image data. The disclosed methods and systems analyze image data for objects such as rectal tubes or stools, or for clusters of suspicious regions, and may eliminate such objects from further analysis prior to presenting potential polyps to a user.

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