updated readme, intro and imprint

haesleinhuepf · Jan 23, 2022 · dc0de57 · dc0de57
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diff --git a/docs/imprint.md b/docs/imprint.md
@@ -6,7 +6,7 @@
 
 Dr. rer. medic. Robert Haase\
 DFG Cluster of Excellence “Physics of Life”, TU Dresden\
-Am Tatzberg 47/49\
+Arnoldstrasse 18\
 01307 Dresden
 
 ### Kontakt
@@ -16,7 +16,7 @@ E-Mail: robert.haase (at] tu-dresden.de
 ### Verantwortlich für den Inhalt nach § 55 Abs. 2 RStV:
 Dr. rer. medic. Robert Haase\
 DFG Cluster of Excellence “Physics of Life”, TU Dresden\
-Am Tatzberg 47/49\
+Arnoldstrasse 18\
 01307 Dresden
 
 # Haftungsausschluss

diff --git a/docs/intro.md b/docs/intro.md
@@ -1,10 +1,19 @@
 # Bio-image Analysis Notebooks
 
 This collection of [Python](https://www.python.org/)
-[jupyter](https://jupyter.org/) notebooks are written for Python beginners who are interested in analysing images acquired using modern fluorescence microscopes. 
+[jupyter](https://jupyter.org/) notebooks are written for Python beginners who are interested in 
+analysing three dimensional images acquired using modern fluorescence microscopes. 
 The journey starts with Python basics and introduces general concepts of bio-image analysis. 
 Special emphasis is put on image data showing cells and nuclei forming tissues and organisms. 
-Demonstrations of basic principles are done in two-dimensional image data and more sophisticated examples demonstrate the basic principles in three-dimensional image data, potentially also over time.
+Demonstrations of basic principles are done in two-dimensional image data and more sophisticated examples demonstrate 
+the basic principles in three-dimensional image data, potentially also over time.
+
+The reader may note that we start with basic python, transit towards standard libraries for image processing such as 
+[scikit-image](http://scikit-image.org/) and [numpy](https://numpy.org/), and from there use increasingly GPU-acceleration libraries such as 
+[pyclesperanto](https://github.com/clEsperanto/pyclesperanto_prototype). 
+The more the content shifts towards three dimensional biological image processing and life-sciences specific quantiative analysis,
+the more we make use of custom open source libraries. These libraries are specialized for processing imaging data showing 
+cells and tissues acquired with fluorescence microscopy.
 
 ## Material origin
 

diff --git a/readme.md b/readme.md
@@ -4,4 +4,4 @@ This repository contains a collection Python Jupyter notebooks exlaining bio-ima
 
 https://haesleinhuepf.github.io/BioImageAnalysisNotebooks
 
-It is build with [Jupyter book](https://jupyterbook.org/intro.html).
+It is maintained using [Jupyter lab](https://jupyterlab.readthedocs.io/en/stable/) and build using [Jupyter book](https://jupyterbook.org/intro.html).
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Expand Up		@@ -4,4 +4,4 @@ This repository contains a collection Python Jupyter notebooks exlaining bio-ima

		https://haesleinhuepf.github.io/BioImageAnalysisNotebooks

		It is build with [Jupyter book](https://jupyterbook.org/intro.html).
		It is maintained using [Jupyter lab](https://jupyterlab.readthedocs.io/en/stable/) and build using [Jupyter book](https://jupyterbook.org/intro.html).