Add announcement for 2nd meeting

_posts/2018-10-22-seminar_2.md

+---
+layout: post
+title:  Deep Learning in Medical and Biological Image and Video Segmentation
+featured-img: empty_auditorium
+---
+
+# Second MLC Meeting on November 8
+
+Our second seminar about machine learning
+will be focused on deep learning in medical and biological image and video
+segmentation. Therefore, we are happy to welcome Walter de Back from the
+Institute for Medical Informatics and Biometry who is an experienced scientist
+in this field. Walter will lead the half-day event including an introduction and
+small lecture as well as a hand on tutorial. The event will be suitable for
+beginners and advanced users in deep learning. 
+
+When: 8th of November from 9 am to 2 pm (including 1 hour lunch break)
+
+Where: Toepler-Bau of TU Dresden, Mommsenstraße 12 in room TOE 203
+
+## Abstract of the seminar
+
+Deep learning has a great potential for biomedical image analysis. In
+particular, convolutional neural networks are an important class of machine
+learning techniques that can be trained to classify, detect, localize, and
+segment objects or abnormalities in different image modalities by learning to
+extract relevant image features. Recent studies have shown that deep
+learning-based systems can outperform human radiologists in accuracy on a
+variety of tasks, at only a fraction of the time and cost. 
+In this seminar, I will provide a gentle introduction to convolutional neural
+networks and their application to biomedical image analysis tasks, highlighting
+both their strengths and limitations. In addition, we will have a hands-on
+session training a neural network to segment biomedical images, based on
+[keras](https://keras.io/).
+
+## About Walter de Back
+
+Walter de Back has an MSc in Artificial Intelligence from Utrecht University
+(NL) and obtained a PhD in Computational Biology from TU Dresden for studies on
+pattern formation in tissues using multi-scale computational modeling. Walter
+now works as a postdoc data scientist at the Faculty of Medicine (TU Dresden)
+where he uses deep learning in a number of projects including cell segmentation
+in live cell microscopy, dental age estimation from panoramic radiographs, and
+tumor tissue classification based on mass spectrometry imaging data. More
+information on: [https://wdeback.gitlab.io/]()