Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Uncertainty: Overview

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

Classification of Leukocytes

Classification of Leukocytes

Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...

Aggregates Classification

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Momentum-dependent multiple gaps in magnesium diboride probed by electron tunnelling spectroscopy.

Nature communications·2012

Same author

Effect of antisense oligodeoxynucleotide targeted against NF-κB/P65 on cell proliferation and tumorigenesis of gastric cancer.

Clinical and experimental medicine·2012

Same author

Innate immunity alone is not sufficient for chronic rejection but predisposes healed allografts to T cell-mediated pathology.

Transplant immunology·2012

Same author

Electroacupuncture improves survival in rats with lethal endotoxemia via the autonomic nervous system.

Anesthesiology·2012

Same author

Single-incision laparoscopic Roux-en-Y hepaticojejunostomy using conventional instruments for children with choledochal cysts.

Surgical endoscopy·2011

Same author

Coherent spin precession via photoinduced antiferromagnetic interactions in La0.67Ca0.33MnO3.

Physical review letters·2011

Same journal

ECG arrhythmia classification via wavelet-driven feature extraction and swarm-optimised gradient boosting.

Computers in biology and medicine·2026

Same journal

Electro-osmotic metachronal cilia transport of viscoelastic blood infused with penta-hybrid nanoparticles in an oviduct: Analytical and neural network modeling.

Computers in biology and medicine·2026

Same journal

sEEGnal: an automated EEG preprocessing pipeline evaluated against expert-driven preprocessing.

Computers in biology and medicine·2026

Same journal

Corrigendum to "Integrating experimental biology, computational methods, and artificial Intelligence in anticancer drug discovery: Bridging the translational Gap" [Comput. Biol. Med. 213 (2026) 111832].

Computers in biology and medicine·2026

Same journal

Organ dose optimization for a point-of-care forearm X-ray photon-counting CT.

Computers in biology and medicine·2026

Same journal

Physics-guided transformation of breathomic feature spaces into disease-specific representations for respiratory disease classification.

Computers in biology and medicine·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Contrastive and uncertainty-aware nuclei segmentation and classification.

Wenxi Liu¹, Qing Zhang¹, Qi Li¹

¹College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China.

Computers in Biology and Medicine

|June 8, 2024

Summary

This summary is machine-generated.

This study introduces novel methods for nuclei segmentation and classification in pathology, improving accuracy for challenging cases like overlapping or small nuclei. The new approach enhances feature representation and classification confidence, leading to state-of-the-art results.

Keywords:

Contrastive learning Deep learning Image segmentation Nuclei classification Nuclei segmentation

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

Related Experiment Videos

Last Updated: Jun 4, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

Area of Science:

Computational pathology
Medical image analysis
Artificial intelligence in healthcare

Background:

Accurate nuclei segmentation and classification are vital for pathology diagnosis.
Challenges include overlapping nuclei, small nuclei misdetection, and pleomorphic nuclei misclassification.

Purpose of the Study:

To enhance feature representativeness and discriminative power for nuclei segmentation and classification.
To address challenges posed by unclear contours of adherent and small nuclei.
To mitigate misclassification due to pleomorphic nuclei and uncertain classification in dense nuclei.

Main Methods:

Nuclei boundary-guided contrastive learning for feature enhancement.
Locality-aware class embedding module for regional category information.
Top-k uncertainty attention module for contextual semantic learning.

Main Results:

The proposed network significantly outperforms existing methods in nuclei segmentation and classification.
Achieved state-of-the-art performance in experimental evaluations.
Demonstrated improved handling of challenging nuclei characteristics.

Conclusions:

The developed methods effectively address key challenges in nuclei analysis.
The network provides a robust solution for accurate pathology diagnosis.
This work advances the field of automated cell analysis in digital pathology.