US 6,549,646 B1 · Divide-and-conquer method and system for the detection of lung nodule in radiological images

Abstract

A divide-and-conquer (DAC) method and system improve the detection of abnormalities, like lung nodules, in radiological images via the use of zone-based digital image processing and artificial neural networks. The DAC method and system divide the lung zone into different zones in order to enhance the efficiency in detection. Different image enhancement techniques are used for each different zone to enhance nodule images, as are different zone-specific techniques for selecting suspected abnormalities, extracting image features corresponding to selected abnormalities, and classifying the abnormalities as either true or false abnormalities.

Claims102

Dependent claims

A method of identifying abnormalities in radiological images of the chest, the method comprising the steps of:

receiving a digital chest image;
discarding pixels outside of the lung zone;
dividing the lung zone into different overlapped zones based on the geometry and subtlety distribution and image characteristics of abnormalities and normal anatomic structure in each zone;
enhancing abnormality signals by using enhancement techniques specifically developed for each zone;
preliminarily selecting suspect abnormalities in each zone;
extracting image features in each zone;
classifying abnormalities and normal anatomic structures in each zone;
integrating outputs from different zones;
and
providing an indication of abnormalities.

7 more elements

A system for identifying abnormalities in radiological images of the chest, comprising:

(a) an image input unit, said image input unit receiving a digital chest image;
(b) a memory unit for storing at least one digital chest image;
(c) an image processing unit that detects said abnormalities, the image processing unit comprising:
an image zoning unit that divides said digital chest image into overlapped zones, thereby generating a zoned image;
a zone-based image enhancement unit that enhances each zone of said zoned image using an enhancement technique tailored to that zone, thereby generating a zone-enhanced image;
a zone-based suspect selection unit that processes each zone of said zone-enhanced image to extract zone-grouped suspect abnormality areas;
a zone-based feature extraction unit that processes said zone-grouped abnormality areas of each zone using a technique tailored to that particular zone, thereby generating zone-grouped suspect features;
a zone-based classification unit that uses different classifiers tailored to the different zones to process said zone-grouped suspect features and to thereby generate suspect classification scores corresponding to said zone-grouped suspect abnormality areas;
and
a zone-based data fusion unit that processes said suspect classification scores associated with said zone-grouped suspect abnormality areas to provide final abnormality areas;
and
(d) an image output unit.

9 more elements

Dependencies are inferred from the claim text.

Divide-and-conquer method and system for the detection of lung nodule in radiological images

Life of this patent

Divide-and-conquer method and system for the detection of lung nodule in radiological images

Life of this patent

Abstract

Claims102