docs: DOC-273: Medical Image Classification template (#6908)

Co-authored-by: caitlinwheeless <caitlin@humansignal.com>

docs/source/templates/gallery_cv.ejs

@@ -65,5 +65,10 @@ cards:
   - Image Classification
   image: "/images/templates-misc/multi-image-classification.png"
   url: "/templates/multi-image_classification.html"
-
+- title: Medical Image Classification and Segmentation
+  categories:
+  - Image Classification
+  - object detection
+  image: "/images/templates/medical-image-classification.png"
+  url: "/templates/medical_imaging_classification.html"
 ---

docs/source/templates/medical_imaging_classification.md

@@ -0,0 +1,87 @@
+---
+title: Medical Image Classification with Bounding Boxes
+type: templates
+category: Computer Vision
+cat: computer-vision
+order: 155
+meta_title: Medical Image Classification with Bounding Boxes Template
+meta_description: Template for classifying medical images and using bounding boxes for image segmentation.
+---
+
+
+<img src="/images/templates/medical-image-classification.png" alt="" class="gif-border" width="552px" height="408px" />
+
+This template interface allows annotators to:
+- Draw bounding boxes around areas identified as tumors in the image using the "Tumor" label.
+- Classify the entire image by selecting one of "Benign", "Malignant", or "Normal".
+
+This setup is useful in medical imaging tasks where you need to localize tumors and also provide an overall assessment of the image.
+
+## Labeling configuration
+
+```xml
+<View>
+  <Image name="image" value="$image"/>
+  <RectangleLabels name="label" toName="image">
+    <Label value="Tumor" background="green"/>
+  </RectangleLabels>
+  <Choices name="classification" toName="image">
+    <Choice value="Benign"/>
+    <Choice value="Malignant"/>
+    <Choice value="Normal"/>
+  </Choices>
+</View>
+```
+
+## About the labeling configuration
+
+#### Image
+
+```xml
+<Image name="image" value="$image"/>
+```
+
+This displays the image. The `value="$image"` means it will use the image field from your task data.
+
+!!! info Tip
+    For example images, you can use a sample dataset available from [kaggle](https://www.kaggle.com/datasets/aryashah2k/breast-ultrasound-images-dataset?resource=download). 
+
+
+#### Bounding boxes
+
+```xml
+<RectangleLabels name="label" toName="image">
+  <Label value="Tumor" background="green"/>
+</RectangleLabels>
+```
+This defines the image segmentation you can use. In this template, you're drawing rectangles (bounding boxes). 
+
+- The `RectangleLabels` tag creates a tool for drawing bounding boxes, and `toName="image"` means that the boxes will be associated with the tag named `image` (which in this example is the name assigned to the `<Image>` tag). 
+- The `Label` tag specifies that the bounding boxes represent "Tumor" regions, displayed with a green background.
+
+For more information about working with bounding boxes, see [Object Detection with Bounding Boxes](image_bbox). 
+
+#### Classification
+
+```xml
+<Choices name="classification" toName="image">
+  <Choice value="Benign"/>
+  <Choice value="Malignant"/>
+  <Choice value="Normal"/>
+</Choices>
+```
+
+This adds image-level classification choices. 
+
+- The `<Choices>` tag provides a set of options for annotators to select.
+- `toName="image"` applies these choices to the entire image.
+- Annotators can classify the image as "Benign", "Malignant", or "Normal".
+
+You can change these classification options by editing them, adding more, or deleting them. If your needs are more complex, you can also use [nested choices](image_classification#Enhance-classification-templates-with-nested-choices). 
+
+
+## Related tags
+
+- [Image](/tags/image.html)
+- [RectangleLabels](/tags/rectanglelabels.html)
+- [Choices](/tags/choices.html)