Update README.md

README.md

@@ -73,7 +73,7 @@ This model is intended for research purposes in the field of neuropathology.
     * Feature extraction for quantitative analysis of neuropathology.  
 ## How to Get Started with the Model
 
-
+The following code examples demonstrate three different approaches to extract embeddings from images using this model. Each approach has specific use cases depending on your requirements.
 Three example methods using Hugging Face `transformers` (adjust based on your actual model and task):
 ```python
 
@@ -209,8 +209,8 @@ if __name__ == "__main__":
     * **Name/Identifier:** UK Alzheimer's Disease Center Neuropathology Whole Slide Image Cohort [BDSA TEST v1.0]
     * **Source:** [UK-ADRC Neuropathology Lab at the University of Kentucky University of Kentucky](https://neuropathlab.createuky.net/), [PLACEHOLDER: Specific Department, Center, or PI, e.g., Sanders-Brown Center on Aging, Department of Pathology]
     * **Description:** [PLACEHOLDER: Describe the data. E.g., "Digitized whole slide images (WSIs) of human post-mortem brain tissue sections from [number] subjects. Sections were stained with [e.g., Hematoxylin and Eosin (H&E), and immunohistochemistry for Amyloid-beta (Aβ) and phosphorylated Tau (pTau)]. Images were acquired using [e.g., Aperio AT2 scanner at 20x magnification]."]
-    * **Preprocessing:** [PLACEHOLDER: Describe significant preprocessing steps. E.g., "WSIs were tiled into non-overlapping [e.g., 224x224 pixel] patches. Tiles with excessive background or artifacts were excluded. Color normalization using [Method, e.g., Macenko method] was applied."]
-    * **Annotation (if applicable for supervised fine-tuning or evaluation):** [PLACEHOLDER: Describe the annotation process. E.g., "Regions of interest (ROIs) for [pathologies] were annotated by board-certified neuropathologists. For classification tasks, slide-level or region-level labels for [disease/pathology presence/severity] were provided."]
+    * **Preprocessing:** WSIs were tiled into non-overlapping 224x224 pixel patches at multiple magnification levels (40x, 10x, 2.5x, and 1.25x). For each magnification level, a maximum of 1000 tiles per annotation label were extracted to ensure balanced representation across pathological features.
+    * **Annotation :** "Regions of interest (ROIs) for Gray Matter, White Matter, Leptomeninges, Exclude and Superficial were annotated by board-certified neuropathologists."
 
 ## Training Procedure