Bell Jar

With the increase in high resolution imaging for histological analyses, Alec Soronow and colleagues from the Kim Neuroscience Lab at UC Santa Cruz have developed Bell Jar, a semiautomated approach for histological analyses for mouse brain tissue. It is easily installable desktop software with tools written in Python, and is user-friendly for researchers without any computational background. It aligns tissue sections based on anatomical structures to a reference atlas (Allen Brain CCF) and offers various tools related to alignment, detection, and counting, due to its ability to detect fluorescent markers. It is also capable of high precision even when tissue is damaged. Bell Jar offers a solution to streamline processing large data sets, with only minor tuning needed from users.

This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID:SCR_026912