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Improved segmentation of nodules for computer assisted diagnosis

A computer-aided, computer-based technology, applied in computing, image analysis, image enhancement, etc., can solve problems such as difficult to achieve high performance

Inactive Publication Date: 2007-06-20
西门子共同研究公司 +1
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AI Technical Summary

Problems solved by technology

Such local approaches may be more efficient than global approaches, but are more difficult to achieve high performance due to the limited amount of information available on non-target structures

Method used

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  • Improved segmentation of nodules for computer assisted diagnosis
  • Improved segmentation of nodules for computer assisted diagnosis
  • Improved segmentation of nodules for computer assisted diagnosis

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Embodiment Construction

[0019] Embodiments may provide robust segmentation of pulmonary nodules in computed tomography (CT) by improving segmentation of conditions near the pleura. By examining the segmentation results, the vicinity of the pleura can be identified. Incorrect segmentation due to surrounding structures can be avoided by modification. Modifications are provided by local non-target removal and / or avoidance methods for near-pleural conditions. In one approach, lung wall regions within the input subvolume are detected and removed. For example, a three-dimensional binary morphological opening operation is used. By using scan data to identify structural elements such as data-driven ellipsoidal 3D structural elements, morphological manipulations are more likely to result in the removal of unwanted information. In another approach, the extended mean shift framework includes repelling (negative) priors that tend towards convergence away from one or more particular data points. This prior-co...

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Abstract

By testing for nodule segmentation errors based on the scan data, juxtapleural cases are identified. Once identified, the scan data or subsequent estimation may be altered to account for adjacent rib, tissue, vessel or other structure effecting segmentation. One alteration is to shape a filter as a function of the scan data. For example, an originally estimated ellipsoid for the nodule segmentation defines the filter. The filter is used to identify the undesired information, and masking removes the undesired information for subsequent estimation of the nodule segmentation. Another possible alteration biases the subsequent estimation away from the incorrect information, such as the rib, tissue or vessel information influencing the original estimation. For example, a negative prior or probability is assigned to data corresponding to the originally estimated segmentation for the subsequent estimation.

Description

[0001] related application [0002] This patent document claims the benefit of the filing date pursuant to 35 U.S.C. § 119(e) of Provisional US Patent Application Serial No. 60 / 672,277, filed April 18, 2005, which is hereby incorporated by reference. technical field [0003] This embodiment involves segmentation. In particular nodules or other structures are identified from scan data such as computed tomography data. Background technique [0004] Lung nodule segmentation is a goal of computer-aided diagnosis (CAD) for identifying lung tumors. For example, CAD systems identify lung nodules from chest computed tomography (CT) data. A semi-automated robust segmentation solution enables reliable volumetric measurement of nodules as part of lung cancer screening and management. [0005] In CAD systems, brightness-based segmentation solutions, such as local density maximum algorithms, segment nodules. Although such solutions can perform satisfactorily for solitary nodules, the...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
Inventor K·奥卡达A·克里什南V·拉梅什M·K·辛U·阿克德米尔
Owner 西门子共同研究公司
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