Medical Imaging
Testings of spectrozonal analog lab-on-a-chip with angle-sensitive pixels (ASP) using diode laser sources in combined nanosecond reflectometric and stroboscopic oscilloscopic measurements.
FILE 1: Combined nanosecond reflectometric and stroboscopic oscilloscopic analysis for RF lab-on-a-chip.mp4
00:15 - Wavelength: 405 nm (DPSS);
00:57 - Wavelength: 650 nm (laser diode source);
FILE 2: Analog angle-sensitive pixel lab-on-a-chip testing using nanosecond stroboscopic oscilloscope.mp4
00:20 - Zero Point Calibration (ZPC);
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167 Views
In this study, adaptive hybrid (AH) scheme is proposed to enhance the measurement accuracy of conventional CD method to acquire the 2-dimensional velocity field of blood flows. It can offer the assistance of the velocity field information measured preliminarily using ultrasound speckle image velocimetry (SIV) technique. Consequently, erroneous vectors in the CD results were replaced with the SIV results. The performance of the proposed AH method was validated by varying flow rate and insonation angle. We compared the AH method with the CD and SIV methods in an agarose vessel model.
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285 Views
Background: Retinopathy of prematurity (ROP) is one of the main causes of childhood blindness. However, insufficient ophthalmologists are qualified for ROP screening.
Objective: To evaluate the performance of a deep neural network (DNN) for automated screening of ROP.
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2289 Views
A sample of synthetic noise-free reference image created by combining multiple instances of structurally preserved cilia cross-sections. The author has removed the dataset, the interested users can contact the author via email: amitsuveer@gmail.com
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243 Views
This dataset is for the paper titled: Segmentation of Cervical Cell Images based on Generative Adversarial Networks. The dataset is used to train and test the Cell-GAN, a generative adversarial network. After training, the Cell-GAN is able to generate a complete single-cell image which has the similar contour to the cell to be segmented.
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1496 Views
For the development and evaluation of organ localization methods, we build a set of annotations of organ bounding boxes based on the MICCAI Liver Tumor Segmentation (LiTS) challenge dataset. Bounding boxes of 11 body organs are included: heart (53/28), left lung (52/21), right lung (52/21), liver (131/70), spleen (131/70), pancreas (131/70), left kidney (129/70), right kidney (131/69), bladder (109/67), left femoral head (109/66) and right femoral head (105/66). The number in the parentheses indicates the number of the organs annotated in training and testing sets.
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4052 Views
We make our dataset publicly avaiable. It consists of 50 H&E stained histopathology annotated images at the nuclei level. This dataset is ideal for those who want an exhaustive annotation of H&E breast cancer patient from a Tripple Negative Breast Cancer cohort.
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2733 Views
Access the dataset for images of typical diabetic retinopathy lesions and also normal retinal structures annotated at a pixel level, focused on an Indian population. This dataset provides information on the disease severity of diabetic retinopathy, and diabetic macular edema for each image.
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118618 Views
Interventional applications of photoacoustic imaging typically require visualization of point-like targets, such as the small, circular, cross-sectional tips of needles, catheters, or brachytherapy seeds. When these point-like targets are imaged in the presence of highly echogenic structures, the resulting photoacoustic wave creates a reflection artifact that may appear as a true signal. We propose to use deep learning techniques to identify these type of noise artifacts for removal in experimental photoacoustic data.
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3171 Views
These datasets were used to produce the results of the following TMI paper: "3D Quantification of Filopodia in Motile Cancer Cells", Castilla C., et al. (2019). IEEE Transactions on Medical Imaging 38(3):862,872.
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699 Views