MEDICAL IMAGE PROCESSING APPARATUS AND METHOD
A medical image processing apparatus comprising processing circuitry configured to: receive computed tomography (CT) perfusion image data that is representative of an anatomical region of a patient or other subject, determine or define a region of interest of the anatomical region, in-paint one or more parts of the anatomical region, the one or more parts being located inside and/or outside of the region of interest and perform low-pass filtering of at least the region of interest to generate filtered CT perfusion image data.
1 . A medical image processing apparatus comprising processing circuitry configured to:
receive computed tomography (CT) perfusion image data that is representative of an anatomical region of a patient or other subject;
determine or define a region of interest of the anatomical region;
in-paint one or more parts of the anatomical region, the one or more parts being located inside and/or outside of the region of interest; and
perform low-pass filtering of at least the region of interest to generate filtered CT perfusion image data.
2 . The apparatus according to claim 1 , wherein the CT perfusion image data comprises perfusion image data obtained from a CT subtraction method or a dual-energy CT method.
3 . The apparatus according to claim 1 , wherein the processing circuitry is configured to in-paint the one or more parts of the anatomical region and perform the low-pass filtering of at least the region of interest sequentially.
4 . The apparatus according to claim 1 , wherein the processing circuitry is configured to in-paint the one or more parts of the anatomical region and perform the low-pass filtering of at least the region of interest simultaneously.
5 . The apparatus according to claim 1 , wherein the processing circuitry is configured to determine the one or more parts of the anatomical region prior to in-painting the one or more parts of the anatomical.
6 . The apparatus according to claim 1 , wherein the processing circuitry is configured to in-paint the one or more parts of the anatomical region based on one or more pixels surrounding or neighbouring the one or more parts of the anatomical region.
7 . The apparatus according to claim 1 , wherein the processing circuitry is configured to perform a first masking process to mask the region of interest.
8 . The apparatus according to claim 1 , the processing circuitry is configured to perform a second masking process to mask the one or more parts of the anatomical region that are located outside and/or inside of the region of interest.
9 . The apparatus according to claim 8 , wherein the processing circuitry is configured to in-paint the masked one or more parts of the anatomical region that are located outside and/or inside of the region of interest.
10 . The apparatus according to claim 1 , wherein the processing circuitry is configured to receive further CT image data that is representative of the anatomical region the patient or other subject.
11 . The apparatus of claim 10 , wherein the processing circuitry is configured to perform a first masking process to mask the region of interest and/or a second masking process to mask the one or more parts of the anatomical region that are located outside and/or inside of the region of interest based on the CT perfusion image data and the further CT image data.
12 . The apparatus according to claim 1 , wherein the processing circuitry is configured to perform the low-pass filtering using a three-dimensional Gaussian filter function.
13 . The apparatus according to claim 1 , wherein the region of interest comprises lung parenchyma of the patient or other subject.
14 . The apparatus according to claim 13 , wherein the one or more parts of the anatomical region that are located inside the region of interest comprise one or more vessels of the lung parenchyma.
15 . The apparatus according to claim 1 , wherein the one or more parts of the anatomical region that are located outside the region of interest comprise one or more vessels of a lung and/or a heart of the patient or other subject.
16 . The apparatus according to claim 1 , wherein the processing circuitry is configured to generate a two-dimensional image based on the filtered CT perfusion image data.
17 . The apparatus according to claim 16 , wherein the two-dimensional image comprises a ventilation-perfusion image.
18 . A medical image processing method comprising:
receiving computed tomography (CT) perfusion image data that is representative of an anatomical region of a patient or other subject;
determining or defining a region of interest of the anatomical region;
in-painting of the one or more parts of the anatomical region, the one or more parts being located inside and/or outside of the region of interest; and
performing low-pass filtering of at least the region of interest to generate filtered CT perfusion image data.
19 . A method of detecting a defect or abnormality in an anatomical structure or organ of a patient or other subject, the method comprising:
receiving filtered CT perfusion image data that is representative of the anatomical structure or the organ of the patient or other subject from a medical image processing apparatus according to claim 1 ;
detecting the defect or abnormality in the anatomical structure or organ using at least one of:
a trained machine learning model; and
an image processing circuitry configured to detect one or more parts of the anatomical structure or organ that exhibit perfusion below a threshold that is associated with an adequate level of perfusion.
20 . The method of claim 19 , wherein the image processing circuitry is configured to detect one or more objects or regions in the filtered CT perfusion image data that are formed from two or more connected pixels.