The migration of cancer cells is highly regulated by the biomechanical properties of their local microenvironment. Using 3D scaffolds of simple composition, several aspects of cancer cell mechanosensing (signal transduction, EMC remodeling, traction forces) have been separately analyzed in the context of cell migration. However, a combined study of these factors in 3D scaffolds that more closely resemble the complex microenvironment of the cancer ECM is still missing.

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The datasets is made of a number of zip files. The name of the file identifies the figure (and figure panel) that the data refers to.

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118 Views

Optical coherence tomography angiography (OCTA) is a novel and high-profile imaging modality that allows a micron-level resolution to present the three-dimensional structure of retinal blood vessels and microvascular systems, and has become an essential tool for retinal vasculature research.

We will pre-upload encryption dataset firstly, and the password will be released later in our paper.

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An OCTA open access dataset for research only!

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245 Views

CHALLENGE ON ULTRASOUND BEAMFORMING WITH DEEP LEARNING (CUBDL)

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Some examples of the non-public data set ImageCLEF 2019 VQA-Med, including training, validation and test part.

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This dataset was used to investigate numerical methods of integration of the Frenet-Serret equations as applied to the study of vessel shape.  This data is a compliation of previously published data from the following papers:

A. V. Kamenskiy, J. N. MacTaggart, I. I. Pipinos, et al., “Three-dimensional geometry of the human carotid artery,” Journal of Biomechanical Engineering, vol. 134, no. 6, p. 064592, 2012.

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Data is organized by the publication from which it originated.  Each folder contains one or more csv files for either the individual vessel described in the file/folder name, or a collection of vessels corresponding to the patient imaged.  See original publications for further details regarding each dataset.  Within each .csv is, at a minimum, the x,y, and z vessel centerline coordinates, post processing.

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Features Extracted from BraTS 2012-2013

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An accurate analysis of fluid–structure interaction (FSI) at compliant arteries via ultrasound (US) imaging and numerical modeling is a limitation of several studies. In this study, we propose a deep learning-based boundary detection and compensation (DL-BDC) technique that can segment vessel boundaries by harnessing the convolutional neural network and wall motion compensation in near-wall flow dynamics. The segmentation performance of the technique is evaluated through numerical simulations with synthetic US images and in vitro experiments.

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103 Views

The presented database contains thermal images (thermograms) of the plantar region. The database was obtained from 122 subjects with a diabetes diagnosis (DM group) and 45 non-diabetic subjects (control group). The relevance of this database consists in to study how the temperature is distributed in the plantar region of both groups and how their differences can be measured. Previous reports in the literature have established that an increase in the plantar temperature is associated with a higher ulceration risk.

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The files are organized in folders with unique nomenclature: two letters to indicate the group (CG for the control group and DM for the diabetic group), three digits to number the folder and the last letter indicating the subject gender (male (M) or female (F)). In each folder, thermograms of the left and right foot (*.png) are provided separately following the same name of the folder plus a letter indicating L (left) or R (right) foot, e. g. CG001_F_L.png. RGB thermograms are only illustrative since these do not contain direct temperature information but they provide a thermal map by using a false-color palette. For obtaining the temperature value associated with each pixel refer to the corresponding *.csv file (e. g. CG001_F_L.csv).  You can graph the *.csv file as an image and use any other color palette for visualizing the temperature map. The plantar analysis made in the associated work (same name of the database in IEEE Access Journal) and in other associated works (refer to the corresponding author link) have used the angiosome division of the plantar region. Then in each folder, there is a subfolder containing four images (*.png and *.csv) that correspond to the four plantar angiosomes of each foot. The same nomenclature is used with the inclusion of three letters at the end, indicating the angiosome LCA, LPA, MCA and MPA (e. g. CG001_F_L_MPA.csv) [1-2].  For each subject, the database contains 20 files, (10 *.png  images and 10 *.csv files), for a total of 1670 RGB images and 1670 temperature files. The database is expected to provide a valuable source to increase research about the potential of infrared thermography for the early diagnosis of diabetic foot problems [3-4], allowing the development of more powerful techniques. The script generate_thermogram.m (MATLAB) is provided for generating a 3D visualization of the data. Some related works are listed below:

 

[1] Peregrina-Barreto, H., Morales-Hernandez, L. A., Rangel-Magdaleno, J. J., Avina-Cervantes, J. G., Ramirez-Cortes, J. M., & Morales-Caporal, R. (2014). Quantitative estimation of temperature variations in plantar angiosomes: a study case for diabetic foot. Computational and mathematical methods in medicine2014.

[2] Hernandez-Contreras, D., Peregrina-Barreto, H., Rangel-Magdaleno, J., Gonzalez-Bernal, J. A., & Altamirano-Robles, L. (2017). A quantitative index for classification of plantar thermal changes in the diabetic foot. Infrared Physics & Technology81, 242-249.

[3] Hernandez-Contreras, D., Peregrina-Barreto, H., Rangel-Magdaleno, J., & Gonzalez-Bernal, J. (2016). Narrative review: Diabetic foot and infrared thermography. Infrared Physics & Technology78, 105-117.

[4] Hernandez-Contreras, D. A., Peregrina-Barreto, H., Rangel-Magdaleno, J. D. J., & Orihuela-Espina, F. (2019). Statistical Approximation of Plantar Temperature Distribution on Diabetic Subjects Based on Beta Mixture Model. IEEE Access7, 28383-28391.

 

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1052 Views

This dataset contains 91 computed tomography pulmonary angiograms positive for pulmonary embolism. At least one experience radiologist has segmented all clots in each of the scans. The dataset was originated for the ISBI challenge cad-pe.

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Each image in images.zip has a mask segmentation with the same name in rs.zip. Each emboli in each mask is numbered.

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207 Views

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