Update README.md

README.md

@@ -40,7 +40,7 @@ ImageJ macros and scripts written at the imaging facility MRI. Have a look at th
 <img align='right' src="https://github.com/MontpellierRessourcesImagerie/imagej_macros_and_scripts/assets/7602420/6c5446cc-d436-4454-898d-bc268e4b5fe8" height='100'/> Analyze the clustering behavior of nuclei in DAPI stained images. The nuclei are detected as the maxima in the image. Using a threshold intensity value, maxima below the threshold are eliminated. The resulting points are clustered using the DBSCAN algorithm. The nearest neighbor distances between all nuclei, and those outside and inside of the clusters are calculated. 
 ####   [Cochlea Hair Cell Counting](https://github.com/MontpellierRessourcesImagerie/imagej_macros_and_scripts/wiki/Cochlea-Hair-Cell-Counting)
 
-<img align='right' src="https://camo.githubusercontent.com/a1a6e3a9e2e8e51238f94f6bfd5ac84d30b6999ec5225f3359a78d82823afcaa/68747470733a2f2f6465762e6d72692e636e72732e66722f6174746163686d656e74732f646f776e6c6f61642f313731322f70726f6a656374696f6e2d6f662d63656c6c732d696d6167652d776974682d636f63686c65612d73656c65637465642e706e67" height='100'/> The aim of this tool is to count the hair cells in sections of 200µm from the apex of the cochlear to its base. The tool needs two types of input images: the 3d stack of the hair cells and a binary mask created from this stack by using the spot detection algorithm of Imaris (Bitplane). After the detection of the spots the background has been set to 0 and the volumes of the spots to 255 and the image has been exported as a tif-series. The tool allows to make the MIP-projections of the two kinds of input images in batch mode. 
+<img align='right' src="https://github.com/MontpellierRessourcesImagerie/imagej_macros_and_scripts/assets/7602420/a820cda3-1e65-4fe2-a21c-6229a7ac5545" height='100'/> The aim of this tool is to count the hair cells in sections of 200µm from the apex of the cochlear to its base. The tool needs two types of input images: the 3d stack of the hair cells and a binary mask created from this stack by using the spot detection algorithm of Imaris (Bitplane). After the detection of the spots the background has been set to 0 and the volumes of the spots to 255 and the image has been exported as a tif-series. The tool allows to make the MIP-projections of the two kinds of input images in batch mode. 
 ####   [Count Axonal Projections Tool](https://github.com/MontpellierRessourcesImagerie/imagej_macros_and_scripts/wiki/Count-Axonal-Projections-Tool)
 
 <img align='right' src="https://camo.githubusercontent.com/e87acfaf56e95c80511ec4f77c35f1af6919a083/687474703a2f2f6465762e6d72692e636e72732e66722f6174746163686d656e74732f646f776e6c6f61642f323231392f70726f6a656374696f6e732e706e67" height='100'/> Count the number of axonal projections that cross a given line. The tool detects and counts the maxima along a line-selection, for example a segmented line.