Medical Image Tumor Detection Around Organ Cavity Boundaries
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Solution Overview
Problem
Existing methods struggle to accurately detect tumors in medical images when cavities are present in the organ, as the partial volume effect can cause erroneous detection of tumor regions.
Innovation Solution
An image processing device that utilizes a detector to extract organ and tumor candidate regions, a generator to create non-organ regions, and a decision unit to determine the overlap ratio between these regions, removing erroneously detected tumor candidates based on their alignment and overlap with non-organ regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tumor detection methods are used on medical images, then tumors can be detected in normal organs, but erroneous detection occurs when cavities are present due to partial volume effect
Solution Approach 1:
The patent segments the medical image into multiple regions: organ regions, non-organ regions, and boundary regions. By dividing the image processing into distinct segments, the system can apply different processing strategies to each region, thereby improving tumor detection accuracy while avoiding erroneous detections in cavity areas.
Solution Approach 2:
The patent extracts and identifies boundary regions that exhibit partial volume effects, separating them from genuine tumor regions. By taking out the problematic boundary regions for special handling, the system eliminates the source of erroneous detection while preserving true tumor detections.
2Productivity
If image processing is performed to detect tumor candidates, then detection speed is improved, but false positives increase in regions with partial volume effects
Solution Approach 1:
The patent performs preliminary identification of boundary regions and non-organ regions before final tumor detection. By preparing these region masks in advance, the system can quickly exclude false positive areas during the detection process, maintaining high detection speed while reducing false positives.
Solution Approach 2:
The patent introduces boundary region masks and non-organ region masks as intermediary elements that mediate between the raw image data and the final tumor detection results. These masks act as filters that prevent false positives from reaching the final detection output.
Data Source
Figure 1A~1C
Figure 2
Figure 3A~3B
AI summary
An image processing method is executed by a computer and the method includes: extracting an organ region representing an organ and a tumor candidate region having a feature for identifying a tumor in the organ from image data obtained by capturing an image of the organ; generating a non-organ region representing a region where the organ is not present using the image data; and removing, from the extracted tumor candidate region, a tumor candidate region being present only at an outer edge portion of the non-organ region in the organ region.