Update README.md

README.md

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-<h2 align="center">Evolutionary design of explainable algorithms for biomedical image segmentation</h2>
-<h4 align="center">Kartezio Official Python Package</h4>
+[![Discord Channel](https://dcbadge.limes.pink/api/server/uwFwHyRxub)](https://discord.gg/KnJ4XWdQMK)
 
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+<h1 align="center">Kartezio: Evolutionary design of explainable algorithms for biomedical image segmentation</h1>
 
-**Kartezio** is a modular Cartesian Genetic Programming (CGP) framework that enables the automated design of fully interpretable image-processing pipelines, without the need for GPUs or extensive training datasets. Built on top of [OpenCV](https://opencv.org/), Kartezio empowers researchers, engineers, and practitioners to discover novel computer vision (CV) solutions using only a handful of annotated samples and a single CPU core.
 
-Originally developed for biomedical image segmentation, Kartezio has been successfully showcased in [Nature Communications](https://www.nature.com/articles/s41467-023-42664-x). Although it shines in medical and life science applications, Kartezio’s underlying principles are domain-agnostic. Whether you’re working with industrial quality control, satellite imagery, embedded vision, or robotics, Kartezio helps you craft custom CV pipelines that are **transparent, fast, frugal  and efficient**.
+**Kartezio** is a modular Cartesian Genetic Programming (CGP) framework that enables the automated design of fully interpretable image-processing pipelines, without the need for GPUs or extensive training datasets.  
+Built on top of [OpenCV](https://opencv.org/), Kartezio empowers researchers, engineers, and practitioners to discover novel computer vision (CV) solutions using only a handful of annotated samples and a single CPU core.
+
+Originally developed for biomedical image segmentation, Kartezio has been successfully showcased in [Nature Communications](https://www.nature.com/articles/s41467-023-42664-x). Although it shines in medical and life science applications, Kartezio’s underlying principles are domain-agnostic.   
+Whether you’re working with industrial quality control, satellite imagery, embedded vision, or robotics, Kartezio helps you craft custom CV pipelines that are **transparent, fast, frugal  and efficient**.
 
 ## Key Features
 
-:nut_and_bolt: **Modular and Customizable**  
+:nut_and_bolt:   **Modular and Customizable**  
    Kartezio is built from interchangeable building blocks, called **Components**, that you can mix, match, or replace. Adapt the pipeline to your project’s unique requirements.
 
-:pencil2: **Few-Shot Learning**  
+:pencil2:   **Few-Shot Learning**  
    Forget the need for massive, annotated datasets. Kartezio can evolve solutions from just a few annotated examples, saving both time and computational resources.
 
-:white_check_mark: **Transparent and Certifiable**
+:white_check_mark:   **Transparent and Certifiable**  
    Every pipeline produced is fully transparent. Inspect the exact operations used, understand their sequence, and trust the decisions made by your model.
 
-:earth_africa: **Frugal and Local**  
+:earth_africa:   **Frugal and Local**  
    Run everything on a single CPU, without GPUs or massive compute clusters. This makes Kartezio ideal for edge devices, embedded systems, or scenarios with limited computational resources.
 
-:microscope: **Broad Applicability**  
+:microscope:   **Broad Applicability**  
    While proven in biomedical image segmentation, Kartezio’s methods readily extend to other fields—like industrial machine vision, space imaging, drone footage analysis, or any custom image-based problem.
 
 ## Getting Started