Nuclear Medicine Image Contrast via Region-Specific LUT Normalization
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Solution Overview
Problem
Nuclear medicine images generated using a single look-up table (LUT) often result in poor contrast for regions with low radioisotope concentration, such as the liver, making it difficult to diagnose and detect lesions effectively.
Innovation Solution
The nuclear medicine diagnostic apparatus includes a region of interest (ROI) setting unit and a normalization unit that adjusts the association between count values and pixel values based on the distribution of count values within the ROI, using various normalization methods to enhance contrast and visibility, allowing for the use of the same LUT for both specified and partial imaging regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a predetermined LUT is used for whole body photographing, then high RI concentration regions have high brightness, but low RI concentration regions become poor in contrast
Solution Approach 1:
The imaging region is divided into a specified region and a partial region, with different LUTs applied to each. The specified region uses a first LUT optimized for high RI concentration areas, while the partial region uses a second LUT optimized for low RI concentration areas, thereby resolving the contrast problem in low concentration regions without sacrificing brightness in high concentration regions.
Solution Approach 2:
Different quality characteristics are applied to different parts of the image through region-specific LUTs. The specified region receives a LUT configuration suited for high brightness display, while the partial region receives a LUT configuration optimized for contrast enhancement in low concentration areas, making each region's display characteristics match its diagnostic requirements.
2Measurement precision
If different LUTs are used for specified and partial imaging regions, then contrast in partial regions is improved, but device complexity increases
Solution Approach 1:
The system uses a single display device that can dynamically apply different LUTs to different regions based on the imaging type. The control unit automatically selects and applies the appropriate LUT configuration (first LUT for specified region, second LUT for partial region) without requiring separate display devices or complex manual configuration, thereby reducing operational complexity while maintaining region-specific optimization.
3Measurement precision
If normalization is applied to enhance visibility of low concentration regions, then detection rate of lesions is improved, but processing time increases
Solution Approach 1:
The system pre-calculates and stores multiple LUTs optimized for different regions and concentration levels. During image processing, the control unit simply selects and applies the appropriate pre-prepared LUT based on the imaging type, avoiding the need for time-consuming real-time normalization calculations while still achieving enhanced visibility and improved lesion detection rates.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the visibility of regions with low radioisotope concentration, improving the detection rate of lesions and reducing inter- and intra-observer errors, thereby supporting more accurate and efficient diagnostics.
Implementation Method 1
detect a gamma ray emitted from an RI distributed in a living body with a gamma ray detector provided outside the living body
Data Source
AI summary
According to one embodiment, a nuclear medicine diagnostic apparatus includes a counting unit, a region of interest setting unit, a normalization unit, and an image generation unit. The counting unit counts radiation emitted from radioisotopes in an imaging region of an object. The ROI setting unit sets a region of interest (ROI) in the imaging region. The normalization unit determines association between count values and pixel values of display pixels for the ROI in accordance with a distribution of the count values of the display pixels corresponding to the ROI. The image generation unit generates an image of the ROI based on the association between the count values and the pixel values for the ROI.