Brain-Tumor-Segmentation-And-Classification VS dipy

Compare Brain-Tumor-Segmentation-And-Classification vs dipy and see what are their differences.

Brain-Tumor-Segmentation-And-Classification

Brain Tumor Segmentation And Classification using artificial intelligence (by Rohith04MVK)
Segmentation image-segmentation Deep Learning medical-imaging HacktoberFest resunet
Source Code
Suggest alternative
Edit details

dipy

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging. (by dipy)
diffusion-mri dti tractography tractometry Registration denoising spherical-harmonics dki Tracking contextual-enhancement neuroanatomy Neuroimaging medical-imaging microstructure Machine Learning Python bundles Segmentation patch2self self-supervised-learning
Source Code
dipy.org
Suggest alternative
Edit details
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
Brain-Tumor-Segmentation-And-Classification dipy
3 3
18 669
- 1.0%
3.0 9.9
9 months ago 3 days ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Brain-Tumor-Segmentation-And-Classification

Posts with mentions or reviews of Brain-Tumor-Segmentation-And-Classification. We have used some of these posts to build our list of alternatives and similar projects.

dipy

Posts with mentions or reviews of dipy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-09.
  • How to find diffusion tensor images?
    1 project | /r/neuro | 5 Oct 2022
    I thought I would get the colorful photos and use this python library (dipy)[https://dipy.org/] to transfer the picture to a matrix. So I now I'm kind confused how I'd get the "numbers"/color in the legend next to the matrix photo I linked. Cause it sounds like the colors have no significance to how many neurons are in that portion rather it sounds like the colors or a way to differentiate on section of the brain from another when just looking at the photos.
  • how to convert dti data to matrix?
    1 project | /r/neuro | 15 Sep 2022
  • Jupyter refuses C++
    2 projects | /r/Jupyter | 9 Feb 2022

What are some alternatives?

When comparing Brain-Tumor-Segmentation-And-Classification and dipy you can also consider the following projects:

caer - High-performance Vision library in Python. Scale your research, not boilerplate.

pySBD - 🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.

MONAILabel - MONAI Label is an intelligent open source image labeling and learning tool.

PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

xeus-cling - Jupyter kernel for the C++ programming language

albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

FedCV - FedCV: An Industrial-grade Federated Learning Framework for Diverse Computer Vision Tasks

NIPY - Workflows and interfaces for neuroimaging packages

Brain-Tumor-Segmentation-And-Classification vs caer dipy vs pySBD Brain-Tumor-Segmentation-And-Classification vs MONAILabel dipy vs PaddleHelix Brain-Tumor-Segmentation-And-Classification vs medicaldetectiontoolkit dipy vs xeus-cling Brain-Tumor-Segmentation-And-Classification vs albumentations dipy vs albumentations Brain-Tumor-Segmentation-And-Classification vs FedCV dipy vs NIPY dipy vs MONAILabel