Update README.md

README.md

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 - **Breast Cancer**: 1,875 ultrasound images (binary labels), suitable for cancer detection benchmarks.
 - **Breast**: 780 ultrasound images with binary labels, ideal for evaluating performance in small datasets.
 - **Derma**: 10,015 dermatology images across 7 classes, critical for skin lesion classification.
-- **OrganC & OrganS**: 23,582 and 25,211 CT images respectively, focused on organ classification and segmentation tasks.
+- **OrganC & OrganS**: 23,582 and 25,211 CT images respectively, focused on organ classification task.
 - **Pneumonia**: 5,856 X-ray images for binary classification of lung infections.
 
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 ## 3D Datasets
 
-3D datasets provide volumetric data essential for tasks like segmentation and spatial analysis in medical imaging. These datasets test models' capabilities in handling 3D spatial information.
+3D datasets provide volumetric data essential for spatial analysis in medical imaging. These datasets test models' capabilities in handling 3D spatial information.
 
 ### Overview of 3D Datasets
 
@@ -83,13 +83,13 @@ The 2D datasets span a range of medical imaging modalities and classification ta
 
 ### Insights into 3D Datasets
 
-- **BraTS21**: 585 MRI scans for binary brain tumor classification, testing volumetric segmentation and analysis.
+- **BraTS21**: 585 MRI scans for binary brain tumor classification, testing volumetric analysis.
 - **BUSV**: 186 ultrasound volumes with binary labels, focusing on breast ultrasound imaging.
 - **Fracture**: 1,370 CT volumes in 3 classes, assessing bone fracture detection.
 - **Lung Adenocarcinoma**: 1,050 CT volumes for classifying lung adenocarcinoma subtypes.
 - **Mosmed**: 200 CT volumes for detecting COVID-19-related lung infections.
-- **Synapse**: 1,759 microscope volumes for neural imaging classification and segmentation.
-- **Vessel**: 1,908 MRA volumes for vessel segmentation.
+- **Synapse**: 1,759 microscope volumes for neural imaging classification.
+- **Vessel**: 1,908 MRA volumes for vessel classification.
 - **IXI (Gender)**: 561 MRI volumes labeled by gender, testing demographic classification from brain imaging.
 
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