diff --git a/docs/source/templates/gallery_cv.ejs b/docs/source/templates/gallery_cv.ejs
index 16ac30093776..1e74cfc8031b 100644
--- a/docs/source/templates/gallery_cv.ejs
+++ b/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"
---
\ No newline at end of file
diff --git a/docs/source/templates/medical_imaging_classification.md b/docs/source/templates/medical_imaging_classification.md
new file mode 100644
index 000000000000..2a7d94de7e32
--- /dev/null
+++ b/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.
+---
+
+
+
+
+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
+
+
+
+
+
+
+
+
+
+
+
+```
+
+## About the labeling configuration
+
+#### Image
+
+```xml
+
+```
+
+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
+
+
+
+```
+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 `` 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
+
+
+
+
+
+```
+
+This adds image-level classification choices.
+
+- The `` 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)
diff --git a/label_studio/core/static/templates/medical-image-classification.png b/label_studio/core/static/templates/medical-image-classification.png
new file mode 100644
index 000000000000..a9f6c7f950ea
Binary files /dev/null and b/label_studio/core/static/templates/medical-image-classification.png differ
+
+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
+