typos in brain_autoradiography

showcase/brain-autoradiography.md

@@ -19,12 +19,12 @@ Since the tool is built to be user-friendly, researchers with minimal knowledge
 
 ## What is the showcase?
 
-{% include image.html file="/MBAT_scheme.png" caption="Figure 1. Development of an open source, semi-automated processing pipeline for aligning autoradiography images from mouse brain tissue to study infection-induced neuroinflammation. The python-based pipeline takes input from data generated through Euro-BioImaging and is itself developed by funding from the ISIDORe project and allows users to align the images in a [Napari](https://napari.org/stable/)-based user interface to the [Allen Brain Atlas](https://portal.brain-map.org/). The full code is open source available on GitHub." alt="Image with a central symbolic computer screen with the program MBAT. Arrows flowing in and out of the screen denoting inputs (data generated through Euro-Bioimaging, Funding from ISIDORe project, Tool development wiht Python and Napari) and outputs (Analyzed data and Code deposition on GitHub) of the software." %}
+{% include image.html file="/MBAT_scheme.png" caption="Figure 1. Development of an open source, semi-automated processing pipeline for aligning autoradiography images from mouse brain tissue to study infection-induced neuroinflammation. The python-based pipeline takes input from data generated through Euro-BioImaging and is itself developed by funding from the ISIDORe project and allows users to align the images in a [Napari](https://napari.org/stable/)-based user interface to the [Allen Brain Atlas](https://portal.brain-map.org/). The full code is open source available on GitHub." alt="Image with a central symbolic computer screen with the program MBAT. Arrows flowing in and out of the screen denoting inputs (data generated through Euro-Bioimaging, Funding from ISIDORe project, Tool development with Python and Napari) and outputs (Analyzed data and Code deposition on GitHub) of the software." %}
 
 Neuroinflammation, such as that associated with SARS-CoV-2 or other infectious diseases, can be studied using autoradiography (ARG). With higher resolution than PET, this method visualizes the anatomical distribution of a protein of interest in (animal) tissue to quantify the photostimulated intensity per unit area in brain regions of interest. Depending on the specific marker used, one can study brain inflammation or measure synaptic degeneration. Since inflammation does not occur to the same extent in all areas, it is necessary to examine specific regions of interest. Traditionally, this image analysis is quite laborious, as individual brain regions of interest have to be drawn manually each time, which leads to high heterogeneity between researchers and is additionally very time consuming.
 
 To solve this problem, researcher Zusanna Cocova (Charles University) and Junel Solis, an image analyst at Turku BioImaging, part of the Euro-BioImaging Finnish Advanced Microscopy Node, developed an automatic pipeline for brain autoradiography image analysis, the Mouse Brain Alignment Tool. This image analysis pipeline was initially designed and applied to mouse brain ARG images acquired at the Turku PET Center, part of the Euro-BioImaging Finnish Biomedical Imaging Node, to investigate brain damage caused by COVID-19.
-MBAT is a Python-based software tool that automates the ARG image analysis process, enabling researchers to focus on specific sub-regions of the brain. It includes a  Napari-based user interface that allows ARG slides of mouse brain tissue to be preprocessed and registered to topographical data from Allen Brain Atlas regions. This allows researchers to preprocess their ARG sections using different layout schemes contained in whole-slide images and automatically convert these sections into single images. The included user interface allows the user to match brain sections with the atlas and calculate mean background intensity. MBAT converts data from the Allen Institute’s Mouse Brain Atlas and stores the topographical information of various brain regions in a local database as regions of interest (ROIs), which can then be overlaid onto the ARG image. The user can translate, rotate, scale, and even edit brain region ROIs. The ARG signal for each ROI can be quantified and stored in a data file, enabling the user to process sections in smaller batches and resume the workflow later, rendering the workflow particularly user-friendly. The pipeline is availale for anyone to reuse on {% tool "github" %}.
+MBAT is a Python-based software tool that automates the ARG image analysis process, enabling researchers to focus on specific sub-regions of the brain. It includes a  Napari-based user interface that allows ARG slides of mouse brain tissue to be preprocessed and registered to topographical data from Allen Brain Atlas regions. This allows researchers to preprocess their ARG sections using different layout schemes contained in whole-slide images and automatically convert these sections into single images. The included user interface allows the user to match brain sections with the atlas and calculate mean background intensity. MBAT converts data from the Allen Institute’s Mouse Brain Atlas and stores the topographical information of various brain regions in a local database as regions of interest (ROIs), which can then be overlaid onto the ARG image. The user can translate, rotate, scale, and even edit brain region ROIs. The ARG signal for each ROI can be quantified and stored in a data file, enabling the user to process sections in smaller batches and resume the workflow later, rendering the workflow particularly user-friendly. The pipeline is available for anyone to reuse on {% tool "github" %}.
 
 ## What can you use the tool for?