The material for the Quantitative Big Imaging course at ETHZ for the Spring Semester 2019
Here you can sign up for the projects and here you can discuss with other students about forming teams or other ideas.
Fluorescence signal in neuron cells in the region of the brain responsible for circadian regulation
The idea would be to quantify body movement in videos of people running (head, legs, arms, hips) in order to start to classify different types of runners and ultimately provide feedback. Ideally the work could be transformed into an app on the phone and used by runners everywhere. The idea could also be applied to different sports and physical events.
Currently, only a handful of very experienced researchers can identify individual whales on sight while out on the water. For the majority of researchers, identifying individual whales takes time, making it difficult to effectively target whales for biological samples, acoustic recordings, and necessary health assessments.
Example whale image to identify:
The goal is to automatically measure the ejection fraction of a heart using 4D (3D + time) images of the heart. There are over 17GB of images to analyze and a few hints on the forums on how to use analytical (Fourier method) and Deep Learning approaches.
(Image borrowed from: Andrej Karpathy, http://karpathy.github.io/2015/05/21/rnn-effectiveness/)