DETECTING HAEMORRHAGIC STROKE IN CT IMAGE DATA

• US 20100183211A1
• Filed: 06/17/2008
• Published: 07/22/2010
• Est. Priority Date: 06/20/2007
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Meetz, Kirsten, Young, Stewart, Buelow, Thomas
• Granted Patent: US 9,159,127 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 2576/026 for the brain
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/12 Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 6/501 for diagnosis of the head, e.g. neuroimaging or craniography
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20156 Automatic seed setting
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 2210/41 Medical
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/44 using image operators, e.g. filters, edge density metrics or local histograms

Abstract

The invention relates to a system (100) arranged to delineate the acute intracerebral haematoma in non-contrasted CT images in two stages. The first stage, performed by the extraction unit (110), employs an analysis of gray values of the image data in order to extract the candidate region. The candidate region may comprise both an acute haematoma and other regions having similar gray values, e.g., regions resulting from partial volume effects at the interface of the bony structures of the skull and the brain. The novel second stage, performed by the classification unit (120), analyzes spatial features of the candidate region such as, for example, the size, shape, and connectedness to the skull bone of the candidate region. Using spatial features of the candidate region improves the correctness of classification of the candidate region as a true or false acute haematoma.

Claims

1. A system (100) for identifying an acute haematoma in non-contrasted CT image data, the system comprising:

an extraction unit (110) for extracting a candidate region suspected to be the acute haematoma, based on a first analysis of gray values of the image data; and

a classification unit (120) for classifying the candidate region as a positive or negative acute haematoma, based on a second analysis of spatial features of the candidate region.

2. A system (100) as claimed in claim 1, wherein the extraction unit (110) comprises:

a skull unit (111) for extracting a skull region;

a brain unit (112) for extracting a brain region, based on the extracted skull region; and

a haematoma unit (113) for extracting the candidate region within the brain region.

3. A system (100) as claimed in claim 1, wherein the classification unit (120) comprises:

a topology unit (121) for computing a topological feature of the candidate region; and

/or

a geometry unit (122) for computing a geometrical feature of the candidate region; and

a discrimination unit (123) for classifying the candidate region on the basis of the topological and/or geometrical feature of the candidate region.

4. A system (100) as claimed in claim 1, wherein the topological and/or geometrical feature of the candidate region is computed, based on a distance-based histogram of the mean gray value of the candidate region.

5. A system (100) as claimed in claim 1, wherein the classification unit is arranged to classify the candidate region as an acute intracranial haematoma, acute subdural haematoma, acute epidural haematoma, or partial volume effect.

6. An image acquisition apparatus (500) comprising a system (100) as claimed in claim 1.

7. A workstation (600) comprising a system (100) as claimed in claim 1.

8. A method (400) of identifying an acute haematoma in non-contrasted CT image data, the method comprising:

an extraction step (410) for extracting a candidate region suspected to be the acute haematoma, based on a first analysis of gray values of the image data; and

a classification step (420) for classifying the candidate region as a positive or negative acute haematoma, based on a second analysis of spatial features of the candidate region.

9. A computer program product to be loaded by a computer arrangement, comprising instructions for identifying an acute haematoma in non-contrasted CT image data, the computer arrangement comprising a processing unit and a memory, the computer program product, after being loaded, providing said processing unit with the capability to carry out the tasks of:

extracting a candidate region suspected to be the acute haematoma, based on a first analysis of gray values of the image data; and

classifying the candidate region as a positive or negative acute haematoma, based on a second analysis of spatial features of the candidate region.