3D Scan Image Detail Enhancement via Density Array Projection
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Solution Overview
Problem
CAT scans face challenges in detecting cancer in organs like the pancreas due to the organ's position and surrounding tissue homogeneity, which reduces image detail.
Innovation Solution
A system and method for processing three-dimensional scan data by forming processed density arrays through operations such as subtraction, rotation, and projection, calculating statistics for each pixel, and displaying images with color intensities proportional to these statistics to enhance visibility of internal structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional CAT scan imaging is used, then the scanning process is simple and fast, but the image detail and contrast are insufficient for detecting cancer in organs like the pancreas
Solution Approach 1:
The system performs preliminary actions by acquiring multiple raw density arrays at different time points before final image generation. This allows preprocessing operations such as subtraction and statistical analysis to be performed on the data before projection, enhancing image detail while managing complexity through structured preparation
Solution Approach 2:
The invention transitions from conventional 2D projection imaging to 3D volumetric analysis by forming processed density arrays from multiple raw density arrays and calculating statistics along projection rays. This dimensional enhancement provides superior image detail and contrast for detecting pancreatic cancer
2Loss of information
If multiple processed density arrays are formed and projected with color intensity calculation, then the visualization of internal structures is enhanced, but the processing time and computational load increase
Solution Approach 1:
The system introduces processed density arrays as intermediary structures between raw scan data and final color images. These intermediaries store calculated statistics (mean, maximum, standard deviation) that preserve information while enabling efficient color intensity computation during the projection phase
Solution Approach 2:
Statistical measures are calculated preliminarily for each projection ray before final image generation. This preliminary computation of mean, maximum, and standard deviation values preserves critical information while organizing data for efficient color intensity assignment, reducing overall processing time
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
Improves the visualization of internal structures by enhancing image detail and contrast, aiding in the detection of cancerous tissues within the pancreas and other organs.
Implementation Method 1
projecting the processed density array onto a plane to form an image, the projecting including calculating one or more of a plurality of statistics for each of a set of vectors each corresponding to a pixel of the image
Data Source
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AI summary
A system and method for visualizing data obtained by performing a three-dimensional scan with penetrating radiation. Raw density arrays are formed from the scan, each raw density array being a three-dimensional array. A processed density array is formed by one or more operations, such as taking the difference between two raw density arrays, rotating the processed density array, multiplying the processed density array by a front-lighting array, and projecting the processed density array onto a plane to form an image, the projecting including calculating one or more of a plurality of statistics for each of a set of vectors each corresponding to a pixel of the image, the plurality of statistics including a vector mean, a vector maximum, and a vector standard deviation.