US 2025/0061573 A1Published application

System and method for classifying lesions

AssigneeKoninklijke Philips N.V.

InventorsDINESH MYSORE SIDDU, ANIL PAWAR, SUDIPTA CHAUDHURY, ARUN HEDDESE SHASTRY

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Abstract

A system (100) for classifying lesions comprising an image providing unit (101) for providing a dual-modal image of an imaging region is provided, the dual-modal image comprising a CT image (10, 10′) and a registered PET image (20′), the imaging region including a tissue region of interest comprising a lesion and a reference tissue region. The system further comprises an identifying unit (102) for identifying, in the CT and the PET image, a respective lesion image segment and, in the PET image, a reference image segment. Moreover, the system comprises a normalizing unit (103) for normalizing the lesion image segment in the PET image with respect to the reference image segment, an image feature extracting unit (104) for extracting image feature values from both lesion image segments, and a classifying unit (105) for classifying the lesion based on the extracted values.

Claims15

Dependent claims

System for classifying lesions, comprising:

an image providing unit for providing a dual-modal image of an imaging region, the dual-modal image comprising a (CT) image and a positron emission tomography (PET) image registered to each other, wherein the imaging region includes a) a tissue region of interest comprising a lesion to be classified and b) a reference tissue region comprising healthy tissue,
an identifying unit for identifying, in each of the CT image and the PET image, a respective lesion image segment corresponding to the lesion in the tissue region of interest and, in the PET image, a reference image segment corresponding to the reference tissue region,
a normalizing unit for normalizing the lesion image segment in the PET image with respect to the reference image segment in the PET image,
an image feature extracting unit for extracting values of a set of image features associated with the lesion from the lesion image segment in the CT image and from the normalized lesion image segment in the PET image, and
a classifying unit for classifying the lesion according to its severity based on the extracted image feature values.

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Dependencies are inferred from the claim text.