Update README.md

README.md

@@ -12,11 +12,11 @@ pinned: false
 
 ## Overview
 ![Exmaple of Annotated WSI](cover_picture.png)
-This dataset provides enhanced and corrected Gleason grading annotations for the TCGA PRAD prostate cancer dataset, supported by Region of Interest (ROI)-level spatial annotations. Developed in collaboration with **[Codatta](https://codatta.io)** and **[DPath.ai](https://dpath.ai)**, where  **[DPath.ai](https://dpath.ai)** launched a dedicated community via **[Codatta](https://codatta.io)** to assemble a network of pathologists, this dataset improved accuracies and granularity of information in the original **[TCGA-PRAD](https://portal.gdc.cancer.gov/projects/TCGA-PRAD)** slide-level labels. The collaborative effort enabled pathologists worldwide to contribute annotations, improving label reliability for AI model training and advancing pathology research. Unlike traditional labeling marketplaces, collaborators a.k.a pathologists retain ownership of the dataset, ensuring their contributions remain recognized, potentially rewarded and valuable within the community. Please cite the dataset in any publication or work using the provided citation format to acknowledge the collaborative efforts of **[Codatta](https://codatta.io)**, **[DPath.ai](https://dpath.ai)**, and the contributing pathologists.
+This dataset provides enhanced Gleason grading annotations for the TCGA PRAD prostate cancer dataset, supported by Region of Interest (ROI)-level spatial annotations. Developed in collaboration with **[Codatta](https://codatta.io)** and **[DPath.ai](https://dpath.ai)**, where  **[DPath.ai](https://dpath.ai)** launched a dedicated community via **[Codatta](https://codatta.io)** to assemble a network of pathologists, this dataset improved accuracies and granularity of information in the original **[TCGA-PRAD](https://portal.gdc.cancer.gov/projects/TCGA-PRAD)** slide-level labels. The collaborative effort enabled pathologists worldwide to contribute annotations, improving label reliability for AI model training and advancing pathology research. Unlike traditional labeling marketplaces, collaborators a.k.a pathologists retain ownership of the dataset, ensuring their contributions remain recognized, potentially rewarded and valuable within the community. Please cite the dataset in any publication or work using the provided citation format to acknowledge the collaborative efforts of **[Codatta](https://codatta.io)**, **[DPath.ai](https://dpath.ai)**, and the contributing pathologists.
 
 ## Motivation
-We discovered significant inconsistencies in the diagnostic labels of the TCGA PRAD dataset, where:
-* Some labels could be enhanced with additional opinons (labels).
+We discovered significant opportunities for data improvement in the diagnostic labels of the TCGA PRAD dataset, where:
+* Some labels could be enhanced with additional diagnostic labels a.k.a opinions.
 * Some labels lacked granular descriptions of the Gleason patterns.
 
 This presents a challenge for AI pathology models, as reported high accuracy might reflect learning from improved labels. To address this:
@@ -44,11 +44,11 @@ This dataset includes two primary files:
 |--------------------------|--------|
 | TCGA WSI Total           | 435    |
 | Agree with TCGA label    | 190    |
-| Disagree with TCGA label | 245    |
+| Enhance TCGA label       | 245    |
 > We are currently in the process of uploading data files to meet the quantities mentioned above. This is an ongoing effort to balance community impact and data quality.
 
 
-## Re-Annotation Process
+## Re-Annotation and Labeling Process
 ![workflow of re-annotation and labelingt](workflow_relabling.png)
 1. **Curation of Cases for Enhancement**: An expert committee identified slides requiring review.
 2. **Annotation**: Junior pathologists performed initial ROI-level annotations.
@@ -95,7 +95,7 @@ roi_data.plot()
 Original WSI files can be downloaded from the GDC Portal.
 Match WSI filenames with the `slide_name` column in `PRAD.csv` for integration.
 
-## Example Workflow
+## Example Steps
 Download **[TCGA PRAD](https://portal.gdc.cancer.gov/projects/TCGA-PRAD)** slides from the GDC Portal.
 **Load** [`PRAD.csv`](https://huggingface.co/datasets/Codatta/Refined-TCGA-PRAD-Prostate-Cancer-Pathology-Dataset/blob/main/dataset/PRAD/PRAD.csv) to access corrected labels and reasoning.
 Visualize ROI annotations using the .geojson files.
@@ -106,9 +106,8 @@ This dataset is provided under a **Creative Commons Attribution 4.0 Internationa
 
 ## Credits
 This dataset is a collaboration between:
-* [Codatta](https://codatta.io) and the network of anynmous pathologists
-* [DPath.ai](https://dpath.ai)
-Special thanks to the Hugging Face community for hosting this dataset.
+* [Codatta](https://codatta.io): A platform that brings together a community of anonymous pathologists to collaborate on annotation and labeling tasks.
+* [DPath.ai](https://dpath.ai): The initiator of the project, responsible for defining the task scope, data requirements, quality assurance workflows, and recruiting the initial cohort of expert pathologists.
 
 ## Contact
 For questions, suggestions, or collaborations (launch custom data sourcing and labeling tasks), please reach out via: