AI Article Synopsis
- Radiologists currently assess neoplasm images manually, highlighting the need for improved methods in detecting early-stage liver neoplasm growth.
- There is significant interest in developing image processing algorithms, like the multifunctional one reported, to measure neoplasm growth and liver volume effectively.
- The CADLN tool will allow radiologists to compare computer-generated volumetric data over time, aiding in the assessment of neoplasm progression or regression and enhancing treatment planning.
Article Abstract
To date, radiologists evaluate neoplasm images manually. Currently there is wide spread attention for developing image processing modules to detect and measure early stage neoplasm growth in liver. We report the fundamentals associated with the development of a multifunctional image processing algorithm useful to measure early growth of neoplasm and the volume of liver. Using CADLN, a radiologist will be able to compare computer generated volumetric data in serial imaging of the patients over time, that eventually will enable assessing progression or regression of neoplasm growth and help in treatment planning.
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| http://dx.doi.org/10.1109/EMBC.2012.6346228 | DOI Listing |
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