Biomedical and Health Sciences

Microwave-based breast cancer detection is a growing field that has been investigated as a potential novel method for breast cancer detection. Breast microwave sensing (BMS) systems use low-powered, non-ionizing microwave signals to interrogate the breast tissues. While some BMS systems have been evaluated in clinical trials, many challenges remain before these systems can be used as a viable clinical option, and breast phantoms (breast models) allow for rigorous and controlled experimental investigations.

1.Visualization of convolutional neural network layers for one participant at ROI 301 * 301

2.Convolutional neural network structure analysis in Matlab

3.Convolutional neural network Matlab code

4.Videos of brightness mode (B-mode) ultrasound images from two participants during the recorded walking trials at 5 different speeds

This dataset is taken from 20 subjects over a duration of 1 hour where experiments were done on the upper body bio-impedance with the following objectives:

a)     Evaluate the effect of externally induced perturbance at the SE interface caused by motion, applied pressure, temperature variation and posture change on bio-impedance measurements.

b)     Evaluate the degree of distortion due to artefact at multiple frequencies (10kHz-100kHz) in the bio-impedance measurements.

Recent advances in computational power availibility and cloud computing has prompted extensive research in epileptic seizure detection and prediction. EEG (electroencephalogram) datasets from ‘Dept. of Epileptology, Univ. of Bonn’ and ‘CHB-MIT Scalp EEG Database’ are publically available datasets which are the most sought after amongst researchers. Bonn dataset is very small compared to CHB-MIT. But still researchers prefer Bonn as it is in simple '.txt' format. The dataset being published here is a preprocessed form of CHB-MIT. The dataset is available in '.csv' format.