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Local Chapter project

Detecting Pediatric Acute Lymphoblastic Leukemia using Computer Vision

Computer VisionImage RecognitionDeep LearningDeep Learning / Computer VisionImage Classification
Start date
March 11, 2023
Finish date
April 15, 2023
Project status
completed
Detecting Pediatric Acute Lymphoblastic Leukemia using Computer Vision

Challenge background

In ALL there is an accumulation in the bone marrow of immature lymphocyte precursor cells, called blast cells. Eventually, the production of normal blood cells is affected by this, resulting in a reduction in the number of red cells, normal white cells, and platelets in the blood.

ALL is the only form of leukemia that is more common in children than adults. It is the single most common form of pediatric cancer, accounting for about one-third of all cases in children. About 85% of cases of childhood leukemia are ALL and it occurs in about 400 children in the UK each year. ALL occurs mostly between the ages of about two and four years. Males are affected more often than females at all ages.

Project timeline

  1. 1

    Week 1

    Week 1: Data collection / organisation

  2. 2

    Week 2

    Week 2: Data cleaning / augmentation / engineering

  3. 3

    Week 3

    Explore the images and any augmentations with analysis

  4. 4

    Week 4

    Build and test a computer vision model

  5. 5

    Week 5

    Develop an app for inference

  6. 6

    Week 6

    test

What you'll learn

Data collecting / organisation, Data cleaning / augmentation / engineering, Exploratory Analysis, Building a Computer Vision model, Develop and deploy an app.

Get involved

What to expect from a Local Chapter project

First project

  • Welcomes beginners and experienced practitioners.
  • Focuses on education and collaborative delivery.
  • Produces open-source project work.

Benefits

  • Address a significant real-world problem with your skills.
  • Build your project portfolio.
  • Demonstrate your work to organizations and project partners.

Requirements

  • Working English communication.
  • A learning mindset.
  • Commitment to collaborative project work.