Marker‐controlled watershed for lymphoma segmentation in sequential CT images
Segmentation of lymphoma containing lymph nodes is a difficult task because of multiple
variables associated with the tumor's location, intensity distribution, and contrast to its …
variables associated with the tumor's location, intensity distribution, and contrast to its …
Semiautomatic segmentation of liver metastases on volumetric CT images
J Yan, LH Schwartz, B Zhao - Medical physics, 2015 - Wiley Online Library
Purpose: Accurate segmentation and quantification of liver metastases on CT images are
critical to surgery/radiation treatment planning and therapy response assessment. To date …
critical to surgery/radiation treatment planning and therapy response assessment. To date …
[PDF][PDF] Segmentation of tumor tissue in gray medical images using watershed transformation method.
The new imaging techniques for organic body tissue give more details and information
about the normal and abnormal tissue that help to distinguish the overlap** in margin of …
about the normal and abnormal tissue that help to distinguish the overlap** in margin of …
Level set segmentation of breast masses in contrast-enhanced dedicated breast CT and evaluation of stop** criteria
Dedicated breast CT (bCT) produces high-resolution 3D tomographic images of the breast,
fully resolving fibroglandular tissue structures within the breast and allowing for breast lesion …
fully resolving fibroglandular tissue structures within the breast and allowing for breast lesion …
[PDF][PDF] Early blight disease segmentation on tomato plant using K-means algorithm with swarm intelligence-based algorithm
Early blight commonly attacks the tomato leaf. The drone and image processing
technologies offer a tool to detect the symptom of the tomato disease. One of the stages in …
technologies offer a tool to detect the symptom of the tomato disease. One of the stages in …
Comparison of two‐dimensional and three‐dimensional iterative watershed segmentation methods in hepatic tumor volumetrics
S Ray, R Hagge, M Gillen, M Cerejo, S Shakeri… - Medical …, 2008 - Wiley Online Library
In this work the authors compare the accuracy of two‐dimensional (2D) and three‐
dimensional (3D) implementations of a computer‐aided image segmentation method to that …
dimensional (3D) implementations of a computer‐aided image segmentation method to that …
Towards an automatic tumor segmentation using iterative watersheds
M Mancas, B Gosselin - Medical Imaging 2004: Image …, 2004 - spiedigitallibrary.org
This paper introduces a simple knowledge model on CT (Computed Tomography) images
which provides high level information. A novel method called iterative watersheds is then …
which provides high level information. A novel method called iterative watersheds is then …
Segmentation of breast masses on dedicated breast computed tomography and three-dimensional breast ultrasound images
We present and evaluate a method for the three-dimensional (3-D) segmentation of breast
masses on dedicated breast computed tomography (bCT) and automated 3-D breast …
masses on dedicated breast computed tomography (bCT) and automated 3-D breast …
[PDF][PDF] Classification model for diabetes mellitus diagnosis based on k-means clustering algorithm optimized with bat algorithm
Diabetes mellitus is a disease characterized by abnormal glucose homeostasis resulting in
an increase in blood sugar. According to data from the International Diabetes Federation …
an increase in blood sugar. According to data from the International Diabetes Federation …
Spatially adaptive active contours: a semi-automatic tumor segmentation framework
Purpose Tumor segmentation constitutes a crucial step in simulating cancer growth and
response to therapy. Incorporation of imaging data individualizes the simulation and assists …
response to therapy. Incorporation of imaging data individualizes the simulation and assists …