Publication

Neurite Tracing in Fluorescence Microscopy Images Using Ridge Filtering and Graph Searching: Principles and Validation

Abstract

To assist neurobiologists investigating the molecular mechanisms involved in neurite formation and differentiation, we have developed an interactive technique for the tracing and quantification of elongated image structures. The technique is based on an improved steerable filter for computing local ridge strength and orientation. It also uses a graph-searching algorithm with a novel cost function exploiting these image features to obtain globally optimal tracings between user-defined control points. To compare the performance of the technique to that of the currently used approach of fully manual delineation, four observers traced selected neurites in fluorescence microscopy images of cells in culture, using both methods. The results indicated that the proposed technique yields comparable accuracy in measuring neurite length, significantly improved accuracy in neurite centerline extraction, significantly improved reproducibility and reduced user interaction.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related concepts (32)
Ridge detection
In , ridge detection is the attempt, via software, to locate ridges in an , defined as curves whose points are local maxima of the function, akin to geographical ridges. For a function of N variables, its ridges are a set of curves whose points are local maxima in N − 1 dimensions. In this respect, the notion of ridge points extends the concept of a local maximum. Correspondingly, the notion of valleys for a function can be defined by replacing the condition of a local maximum with the condition of a local minimum.
Feature (computer vision)
In computer vision and , a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
Human–computer interaction
Human–computer interaction (HCI) is research in the design and the use of computer technology, which focuses on the interfaces between people (users) and computers. HCI researchers observe the ways humans interact with computers and design technologies that allow humans to interact with computers in novel ways. A device that allows interaction between human being and a computer is known as a "Human-computer Interface (HCI)".
Show more
Related publications (38)

Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...
2022

Detection and Measurement of Matrix Discontinuities in UHPFRC by Means of Distributed Fiber Optics Sensing

Bartlomiej Wojciech Sawicki, Antoine Bassil

Following the significant improvement in their properties during the last decade, Distributed Fiber Optics sensing (DFOs) techniques are nowadays implemented for industrial use in the context of Structural Health Monitoring (SHM). While these techniques ha ...
2020

SIPS: Unsupervised Succinct Interest Points

Davide Scaramuzza, Titus Cieslewski

Detecting interest points is a key component of vision-based estimation algorithms, such as visual odometry or visual SLAM. Classically, interest point detection has been done with methods such as Harris, FAST, or DoG. Recently, better detectors have been ...
2018
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.