Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Fluorescence anisotropy imaging in drug discovery
C Vinegoni, PF Feruglio, I Gryczynski… - Advanced drug delivery …, 2019 - Elsevier
Non-invasive measurement of drug-target engagement can provide critical insights in the
molecular pharmacology of small molecule drugs. Fluorescence polarization/fluorescence …
molecular pharmacology of small molecule drugs. Fluorescence polarization/fluorescence …
Automatic brain hemorrhage segmentation and classification algorithm based on weighted grayscale histogram feature in a hierarchical classification structure
B Shahangian, H Pourghassem - Biocybernetics and Biomedical …, 2016 - Elsevier
Brain hemorrhage is the first cause of death in ages between 15 and 24, and the third after
heart diseases and cancers in other ages. Saving the lives of such patients completely …
heart diseases and cancers in other ages. Saving the lives of such patients completely …
STL rapid prototyping bio-CAD model for CT medical image segmentation
This paper presents a simple process to construct 3D rapid prototyping (RP) physical
models for computer tomography (CT) medical images segmentation. The use of …
models for computer tomography (CT) medical images segmentation. The use of …
Segmentation of brain from computed tomography head images
Q Hu, G Qian, A Aziz… - 2005 IEEE Engineering in …, 2006 - ieeexplore.ieee.org
An algorithm to determine the human brain (gray matter (GM) and white matter (WM)) from
computed tomography (CT) head volumes with large slice thickness is proposed based on …
computed tomography (CT) head volumes with large slice thickness is proposed based on …
Segmentation of CT brain images using K-means and EM clustering
The combination of the different approaches for the segmentation of brain images is
presented in this paper. The system segments the CT head images into 3 clusters, which are …
presented in this paper. The system segments the CT head images into 3 clusters, which are …
Segmentation of spontaneous intracerebral hemorrhage on CT with a region growing method based on watershed preprocessing
Z Zhou, H Wan, H Zhang, X Chen, X Wang… - Frontiers in …, 2022 - frontiersin.org
Intracerebral hemorrhage (ICH) poses a great threat to human life due to its high incidence
and poor prognosis. Identification of the bleeding location and quantification of the volume …
and poor prognosis. Identification of the bleeding location and quantification of the volume …
Automatic brain hemorrhage segmentation and classification in CT scan images
B Shahangian, H Pourghassem - 2013 8th Iranian Conference …, 2013 - ieeexplore.ieee.org
Brain hemorrhage detection and classification is a major help to physicians to rescue
patients in an early stage. In this paper, we have tried to introduce an automatic detection …
patients in an early stage. In this paper, we have tried to introduce an automatic detection …
Joint segmentation and reconstruction of hyperspectral data with compressed measurements
Q Zhang, R Plemmons, D Kittle, D Brady, S Prasad - Applied optics, 2011 - opg.optica.org
This work describes numerical methods for the joint reconstruction and segmentation of
spectral images taken by compressive sensing coded aperture snapshot spectral imagers …
spectral images taken by compressive sensing coded aperture snapshot spectral imagers …
Outer wall segmentation of abdominal aortic aneurysm by variable neighborhood search through intensity and gradient spaces
Aortic aneurysm segmentation remains a challenge. Manual segmentation is a time-
consuming process which is not practical for routine use. To address this limitation, several …
consuming process which is not practical for routine use. To address this limitation, several …