Current methods in medical image segmentation
▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications,
by automating or facilitating the delineation of anatomical structures and other regions of …
by automating or facilitating the delineation of anatomical structures and other regions of …
[HTML][HTML] Type 2 immunity in asthma
M Caminati, DL Pham, D Bagnasco… - World Allergy …, 2018 - Springer
Type 2-immunity represents the typical adaptive response to allergen exposure in atopic
individuals. It mainly involves Th2 cells and immunoglobulin E, as the main orchestrators of …
individuals. It mainly involves Th2 cells and immunoglobulin E, as the main orchestrators of …
Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain
SM Resnick, DL Pham, MA Kraut… - Journal of …, 2003 - Soc Neuroscience
Age-related loss of brain tissue has been inferred from cross-sectional neuroimaging studies,
but direct measurements of gray and white matter changes from longitudinal studies are …
but direct measurements of gray and white matter changes from longitudinal studies are …
Adaptive fuzzy segmentation of magnetic resonance images
An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional
(3-D) multispectral magnetic resonance (MR) images that have been corrupted by …
(3-D) multispectral magnetic resonance (MR) images that have been corrupted by …
What we learn about bipolar disorder from large‐scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group
…, RA Ophoff, M Ota, BJ Overs, DL Pham… - Human brain …, 2022 - Wiley Online Library
MRI‐derived brain measures offer a link between genes, the environment and behavior and
have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of …
have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of …
[HTML][HTML] An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities
We present a novel algorithm for obtaining fuzzy segmentations of images that are subject
to multiplicative intensity inhomogeneities, such as magnetic resonance images. The …
to multiplicative intensity inhomogeneities, such as magnetic resonance images. The …
[PDF][PDF] Image segmentation using deformable models
In the past four decades, computerized image segmentation has played an increasingly
important role in medical imaging. Segmented images are now used routinely in a multitude of …
important role in medical imaging. Segmented images are now used routinely in a multitude of …
Spatial models for fuzzy clustering
DL Pham - Computer vision and image understanding, 2001 - Elsevier
A novel approach to fuzzy clustering for image segmentation is described. The fuzzy C-means
objective function is generalized to include a spatial penalty on the membership functions. …
objective function is generalized to include a spatial penalty on the membership functions. …
A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions
We describe a new fully automatic method for the segmentation of brain images that contain
multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used …
multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used …
[HTML][HTML] Statistical normalization techniques for magnetic resonance imaging
While computed tomography and other imaging techniques are measured in absolute units
with physical meaning, magnetic resonance images are expressed in arbitrary units that are …
with physical meaning, magnetic resonance images are expressed in arbitrary units that are …