Results 91 to 100 of about 170,175 (308)
Medical image segmentation methods overview
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2018 This article provides an overview of the modern medical image segmentation methods. The most popular methods such as multi-atlas based methods and deep learning approach are considered in more details.
Bohdan V. Chapaliuk, Yuriy P. Zaychenko
doaj +1 more source
Multimodal Evaluation for Medical Image Segmentation [PDF]
, 2007 This paper is a joint effort between five institutions that introduces several novel similarity measures and combines them to carry out a multimodal segmentation evaluation. The new similarity measures proposed are based on the location and the intensity values of the misclassified voxels as well as on the connectivity and the boundaries of the ...
Rubén Cárdenes +7 more
openaire +1 more source
FEBS Letters, EarlyView.Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura +2 more
wiley +1 more source
Contour evolution scheme for variational image segmentation and smoothing [PDF]
, 2007 An algorithm, based on the Mumford–Shah (M–S) functional, for image contour segmentation and object smoothing in the presence of noise is proposed. However, in the proposed algorithm, contour length minimisation is not required and it is demonstrated ...
Sharif, Bayan, Mahmoodi, Sasan
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Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification [PDF]
, 2006 —We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel’s feature vector. Feature vectors are composed of the pixel’
Michael J. Cree +10 more
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FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Advantages of transformer and its application for medical image segmentation: a survey
BioMedical Engineering OnLinePurpose Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models.
Qiumei Pu +4 more
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Active contours with weighted external forces for medical image segmentation [PDF]
Parametric active contours have been widely used for image segmentation. However, high noise levels and weak edges are the most acute issues that hinder their performance, particularly in medical images.
Khadidos, Alaa +2 more
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Hierarchical Models for Image Segmentation: from Color to Texture [PDF]
, 2008 Segmentation is a low-level processing aimed at the partition of an image in disjoint regions, each one homogeneous with respect to some properties like intensity, texture, shape, etc.
Gaetano, Raffaele
core