Object Detection and Statistical Analysis of Microscopy Image Sequences
Confocal microscope images are wide useful in medical diagnosis and research. The automatic interpretation of this type of images is very important but it is a challenging endeavor in image processing area, since these images are heavily contaminated with noise, have low contrast and low resolution...
Main Authors: | Juliana Gambini, Sasha Hurovitz, Debora Chan, Rodrigo Ramele |
---|---|
Format: | Article |
Language: | English |
Published: |
Computer Vision Center Press
2022-04-01
|
Series: | ELCVIA Electronic Letters on Computer Vision and Image Analysis |
Online Access: | https://elcvia.cvc.uab.cat/article/view/1482 |
Similar Items
-
An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural Networks
by: Brian Ezequiel Ail, et al.
Published: (2024-08-01) -
Tracking and detecting objects in image sequence
by: Wang, Li
Published: (2016) -
Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics
by: Thibault Lagache, et al.
Published: (2018-02-01) -
Texture-based statistical models for object detection in natural images
by: Rickert, Thomas D. (Thomas Dale), 1975-
Published: (2013) -
Algorithmic feature detection and statistical analysis in scanning probe microscopy data
by: Toh, Jeremy Wee Siang
Published: (2023)