Skip to main content

splinedist

Project description

SplineDist: Automated Cell Segmentation with Spline Curves

This repository contains the implementation of SplineDist, a machine learning framework for automated cell segmentation with spline curves. The manuscript is accepted at ISBI 2021. The code in its current state allows reproducing the paper experiments but is still in development. We are currently working to package it in a cleaned and optimized form. In the meantime, we encourage interested end-users to contact us for more information and assistance.

Overview

SplineDist has been designed for performing instance segmentation in bioimages. Our method has been built by extending the popular StarDist framework. Our repository relies on the high-quality StarDist repository. We encourage the user to explore StarDist repository for further details on the StarDist method.

While StarDist models objects with star-convex polygonal representation, SplineDist models objects as parametric spline curves. As our representation is more general, it allows to model non-star-convex objects as well, with the possibility of conducting further statistical shape analysis.

Requirements

  1. Tensorflow

  2. StarDist 0.6.2 (can be installed with pip : pip install stardist==0.6.2)

Walkthrough

Three walkthrough notebooks have been included in this repository for data-exploration, training, and inference tasks.

Datasets

The synthetic dataset used in the SplineDist manuscript can be found here.This dataset contains synthetic images with mostly star-convex and some non-star convex cell-like objects.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

splinedist-0.1.2.tar.gz (44.7 kB view details)

Uploaded Source

Built Distribution

splinedist-0.1.2-py3-none-any.whl (49.9 kB view details)

Uploaded Python 3

File details

Details for the file splinedist-0.1.2.tar.gz.

File metadata

  • Download URL: splinedist-0.1.2.tar.gz
  • Upload date:
  • Size: 44.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for splinedist-0.1.2.tar.gz
Algorithm Hash digest
SHA256 72c9f65ed0a11c8f79eb5d1c493d4efd2b7d5ce110658102f2ce11f4f40900b3
MD5 21b83876f6450eb193669d87cfef0298
BLAKE2b-256 fa70439d8159f8aff5c9062babc0e2994b09bf6e4ea6188b268a4304a4562cfc

See more details on using hashes here.

File details

Details for the file splinedist-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: splinedist-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 49.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for splinedist-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 117f6315cce9389ed027772413e61812a2266651115e2dfa376eea35dd6d00a6
MD5 daf7b16b793980ad1ec765e2c126a371
BLAKE2b-256 8b89d7b842b0d37478a3dd29d4a106e6b08702a7fab68f66d5258a4fa73cc002

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page