Datasets
Models
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Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research Project
Acute Myeloid & Lymphoblastic Leukemia Python Classifiers
The Peter Moss Acute Myeloid & Lymphoblastic Leukemia Python classifiers are a collection of classifiers that have been developed by the team and our community using the Python programming language.
These classifiers include Caffe, FastAI, Keras, Movidius, OpenVino, pure Python and Tensorflow classifiers, Each project may have multiple classifiers.
Data Augmentation
The Acute Myeloid & Lymphoblastic Leukemia Classifier Data Augmentation program applies filters to datasets and increases the amount of training / test data.
Python Classifiers
This repository hosts a collection of classifiers that have been developed by the team using the Python programming language. These classifiers include Caffe, FastAI, Movidius, OpenVino, pure Python and Tensorflow classifiers each project may have multiple classifiers.
| Projects | Description | Status |
|---|---|---|
| Caffe Classifiers | AML/ALL classifiers created using the Caffe framework. | Ongoing |
| FastAI Classifiers | AML/ALL classifiers created using the FastAI framework. | Ongoing |
| Keras Classifiers | AML/ALL classifiers created using the Keras framework. | Ongoing |
| Movidius Classifiers | AML/ALL classifiers created using Intel Movidius(NC1/NCS2). | Ongoing |
| OpenVino Classifiers | AML/ALL classifiers created using Intel OpenVino. | Ongoing |
| Pure Python Classifiers | AML/ALL classifiers created using pure Python. | Ongoing |
| Tensorflow Classifiers | AML/ALL classifiers created using the Tensorflow framework. | Ongoing |
Caffe Python Classifiers
The Peter Moss Acute Myeloid & Lymphoblastic Leukemia Python Caffe classifiers are a collection of projects that use computer vision written in Python Caffe to classify Acute Myeloid & Lymphoblastic Leukemia in unseen images.
| Projects | Description | Status |
|---|---|---|
| AllCNN Caffe Classifier | allCNN classifier created using the Caffe framework. | Ongoing |
Intel Movidius/NCS Python Classifiers
This repository hosts a collection of classifiers that have been developed by the team using Python and Intel Movidius NCS/NCS2.
| Project | Description | Status |
|---|---|---|
| Movidius NCS | AML/ALL classifiers created using Intel Movidius NCS. | Ongoing |
| Movidius NCS2 | AML/ALL classifiers created using Intel Movidius NCS2 & OpenVino. | Ongoing |
FastAI Python Classifiers
The Peter Moss Acute Myeloid & Lymphoblastic Leukemia Python FastAI classifier projects are a collection of projects that use computer vision programs written using FastAI to classify Acute Myeloid & Lymphoblastic Leukemia in unseen images.
| Model | Project | Description | Status | Author |
|---|---|---|---|---|
| Resnet | FastAI Resnet50 Classifier | A FastAI model trained using Resnet50 | Ongoing | Salvatore Raieli / Adam Milton-Barker |
| Resnet | FastAI Resnet50(a) Classifier | A FastAI model trained using Resnet50 | Ongoing | Salvatore Raieli / Adam Milton-Barker |
| Resnet | FastAI Resnet34 Classifier | A FastAI model trained using Resnet34 | Ongoing | Salvatore Raieli / Adam Milton-Barker |
| Resnet | FastAI Resnet18 Classifier | A FastAI model trained using Resnet18 | Ongoing | Salvatore Raieli / Adam Milton-Barker |
Keras Python Classifiers
The Peter Moss Acute Myeloid & Lymphoblastic Leukemia Python Keras classifier projects are a collection of projects that use computer vision programs written using Keras to classify Acute Myeloid & Lymphoblastic Leukemia in unseen images.
| Dataset | Project | Description | Status | Author |
|---|---|---|---|---|
| ALL_IDB2 | QuantisedCode | A model trained to detect ALL using Keras with Tensorflow Backend, Paper 1 and the original Dataset 2. | Ongoing | Amita Kapoor & Taru Jain |
| ALL_IDB1 | AllCNN | A model trained to detect ALL using Keras with Tensorflow Backend, Paper 1 and the original Dataset 1. | Ongoing | Adam Milton-Barker |
| ALL_IDB2 | AllCNN | A model trained to detect ALL using Keras with Tensorflow Backend, Paper 1 and the original Dataset 2. | Ongoing | Adam Milton-Barker |
Detecting Acute Lymphoblastic Leukemia Using Caffe, OpenVino & Neural Compute Stick Series
A series of articles / tutorials by Adam Milton-Barker that take you through attempting to replicate the work carried out in the Acute Myeloid Leukemia Classification Using Convolution Neural Network In Clinical Decision Support System paper.
- Introduction to convolutional neural networks in Caffe*
- Preparing the Acute Lymphoblastic Leukemia dataset
Contributing
The Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research project encourages and welcomes code contributions, bug fixes and enhancements from the Github.
Please read the CONTRIBUTING document for a full guide to forking our repositories and submitting your pull requests. You will also find information about our code of conduct on this page.
Team Contributors
The following Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research project team members have contributed towards this repository:
- Adam Milton-Barker - Bigfinite IoT Network Engineer & Intel Software Innovator, Barcelona, Spain
- Salvatore Raieli - PhD Immunolgy / Bioinformaticia, Bologna, Italy
- Dr Amita Kapoor - Delhi University, Delhi, India
Student Program Contributors
The following AML/ALL AI Student Program Students & Research Interns have contributed towards this repository:
- Taru Jain - Pre-final year undergraduate pursuing B.Tech in IT
Versioning
We use SemVer for versioning. For the versions available, see Releases.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Bugs/Issues
We use the repo issues to track bugs and general requests related to using this project.