Update README.md

README.md

@@ -32,6 +32,8 @@ This [repository](https://github.com/PathologyDataScience/BCSS) contains the nec
 
 - Amgad, Mohamed, et al. "NuCLS: A Scalable Crowdsourcing Approach and Dataset for Nucleus Classification and Segmentation in Breast Cancer." GigaScience, vol. 11, 2022, https://doi.org/10.1093/gigascience/giac037. Accessed 18 Mar. 2024.
 
+![](https://huggingface.co/datasets/minhanhto09/NuCLS_dataset/resolve/main/fig1.PNG)
+
 
 ## Accessing the Data
 
@@ -54,8 +56,6 @@ The Corrected Single-Rater Dataset is a collection of 1,744 entries, each with a
 
 A single dataset entry contains the following details:
 
-![An instance of the dataset](https://huggingface.co/datasets/minhanhto09/NuCLS_dataset/blob/main/Image%2017-03-2024%20at%2023.54.jpeg "An instance of the dataset")
-
 - `rgb_image`: A high-resolution RGB image of breast cancer tissue.
 
 - `mask_image`: A mask image with each nucleus labeled. Class labels are encoded in the first channel. The second and third channels are used to create a unique identifier for each nucleus. The field of view (gray area) is marked to delineate the annotated region.
@@ -78,6 +78,7 @@ A single dataset entry contains the following details:
     
     - `coords_x`, `coords_y`: The specific boundary coordinates of the nucleus.
 
+![](https://huggingface.co/datasets/minhanhto09/NuCLS_dataset/resolve/main/Image%2017-03-2024%20at%2023.54.jpeg)
 
 ### Data Split