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Computer-aided detection (CAD) of a disease

A technology of disease and probability, applied in calculation, detailed information related to graphical user interface, image data processing, etc., can solve problems such as false positives, achieve effective calculation and improve calculation speed

Inactive Publication Date: 2010-10-13
KONINK PHILIPS ELECTRONICS NV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There is also a tradeoff between sensitivity and specificity, however, which can lead to an undesirably large number of false positives (FP), or, more seriously, false negatives

Method used

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  • Computer-aided detection (CAD) of a disease
  • Computer-aided detection (CAD) of a disease

Examples

Experimental program
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Embodiment Construction

[0041] figure 1 is a schematic diagram of a combined imaging modality and computer system 1 for one embodiment of the invention. The computer system 1 is arranged to perform CAD on a medical image dataset 20 obtained from a medical imaging modality IM, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET). ), single photon emission computed tomography (SPECT), ultrasound scanning, and rotational angiography or any other medical imaging modality. The transmission from the modality IM to the unit 12 can be via a dedicated connection means 11 (short or remote, possibly via the Internet) or by wireless transmission.

[0042] The unit 12 of the computer system 1 is arranged to perform computer aided detection (CAD) of diseases on the medical image data set 20 . Segmentation means 13 are provided for segmenting the medical image dataset 20 using an anatomical model, preferably an augmented model. For a general reference in medical ...

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Abstract

The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention isadvantageous in that more efficient computations can be performed because the degree ofanalysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region. It is thereby possible to increase computational speed and thereby diseases like cancer, in particular cancer nodules in the lungs, can be more effectively found from medical image analysis.

Description

Background technique [0001] The present invention relates to methods for analyzing medical image datasets obtained from medical imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), Single Photon Emission Computed Tomography (SPECT), Ultrasound Scanning and Rotational Angiography and other medical imaging modalities. The invention also relates to a corresponding computer system and a corresponding computer program product. Background of the invention [0002] In recent years, the development of medical imaging including modalities such as computed tomography (CT) or magnetic resonance imaging (MRI) serves to improve the detection of various types of diseases, in particular cancerous tumors. This advancement in medical imaging has resulted in a large amount of medical image data, which has to be carefully analyzed and evaluated in order to derive reliable diagnostic results therefrom. This phase of analysi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0081G06T7/0012G06T2200/24G06T2207/30061G06T2207/10072G06T7/11
Inventor C·洛伦茨J·冯贝格T·比洛R·维姆克
Owner KONINK PHILIPS ELECTRONICS NV
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