Microsoft Azure AI Fundamentals (AI-900)Describe fundamental principles of machine learning on AzureMedium
A research team is developing an AI system to analyze medical images (e.g., X-rays, MRIs) to precisely delineate organs, tumors, or other anatomical structures. The goal is not just to classify the image as 'diseased' or 'healthy', but to identify the exact boundaries and location of specific regions of interest within the image. Which computer vision task is most appropriate for this objective?
- AImage Segmentation
- BFeature Extraction
- CImage Classification
- DObject Detection
Show answer & explanationAnswer & explanation
Correct answer: A. Image Segmentation
Image segmentation is the computer vision task that involves partitioning an image into multiple segments, often to identify and delineate specific objects or regions at a pixel level. This precisely matches the goal of identifying exact boundaries of organs or tumors.
Why the other options are wrong
- B. Feature Extraction is a general process of deriving features from raw data, not a specific task for delineating objects in images.
- C. Image Classification assigns a single label to the entire image, not pixel-level boundaries.
- D. Object Detection identifies objects within an image and draws bounding boxes around them, but does not provide precise pixel-level boundaries.
Image Segmentation
A computer vision task that involves partitioning a digital image into multiple segments (sets of pixels), often to locate objects and boundaries. It assigns a label to every pixel in an image such that pixels with the same label share certain characteristics.
- Provides pixel-level understanding of an image.
- Used for precise object delineation and boundary detection.
- Common applications include medical imaging, autonomous driving, and satellite image analysis.
Memory trick: Computers seeing and understanding pictures.