Computer assisted detection of liver neoplasm (CADLN).
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.
Department of Biomedical Engineering, University of Bridgeport.
Shrinivas
S
Bhosale
Ashish
A
Aphale
Isaac
I
Macwan
Miad
M
Faezipour
Priya
P
Bhosale
Prabir
P
Patra
D000465:Algorithms; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D011860:Radiography, Abdominal / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*