Results 181 to 190 of about 79,106 (281)

A Label-Free Hyperspectral Imaging Device for Ex Vivo Characterization and Grading of Meningioma Tissues. [PDF]

J Biophotonics
Ricci P, Bonaudo C, Ezhov I, Toaha A, Nardini D, Camelia M, Lucidi F, Nozzoli F, Mach T, Tachtsidis I, Rueckert D, Della Puppa A, Giannoni L, Pavone FS.   +13 more
europepmc   +1 more source

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract PlantCV is an open‐source Python project aimed at developing tools to address a range of image‐based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding ...
Haley Schuhl, Keely E. Brown, Hudanyun Sheng, Parag K. Bhatt, Jorge Gutierrez, Dominik Schneider, Anna L. Casto, Lucia Acosta‐Gamboa, Joe G. Ballenger, Fabio Barbero, Jackson Braley, Autumn M. Brown, Leonardo Chavez, Shannon Cunningham, Malinda Dilhara, Adam M. Dimech, Joseph G. Duenwald, Annika Fischer, Jared M. Gordon, Chloe Hendrikse, Gabriela L. Hernandez, John G. Hodge, Martina Huber, Brandon M. Hurr, Sanaz Jarolmasjed, Karina Medina Jimenez, Samuel Kenney, Grant Konkel, Alexander Kutschera, Sunita Lama, Matthew Lohbihler, Argelia Lorence, Collin Luebbert, Nathaniel Ly, Heather K. Manching, Annarita Marrano, Susan Meerdink, Nicholas M. Miklave, Pavan Mudrageda, Katherine M. Murphy, J. David Peery, Ronald Pierik, Seth Polydore, Caleb Robey, Tess Rogers, Tyler J. Schultz, Eliza Seigel, Dhiraj Srivastava, Stephan Summerer, Josh Sumner, Chong Teng, Adriane E. Thompson, Jose C. Tovar, Tim van Daalen, Mark Watson, John J. Wheeler, Mark C. Wilson, Kaitlyn R. Ying, Alina Zare, Yutai Zhou, Malia A. Gehan, Noah Fahlgren   +61 more
wiley   +1 more source

Introducing OpenTextile-NIR: Near-infrared hyperspectral imaging and photography dataset for optical identification of textiles. [PDF]

Data Brief
Sormunen T, Mahlamäki E, Mäkelä SM, Mäkelä M.   +3 more
europepmc   +1 more source

A systematic color correction pipeline for controlled‐environment imaging

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
ABSTRACT We present a stepwise color correction (CC) pipeline for controlled imaging environments. The workflow integrates flat‐field correction (FFC), gamma correction, and white‐balance correction, followed by a color‐mapping (CM) stage using machine‐learning regression—linear, partial least squares, and neural networks (NNs)—to deliver reliable CC ...
Collins Wakholi, Michael A. Hardigan, Jungmin Lee, Scott B. Lukas, Max J. Feldman, Kayla R. Altendorf, Jeffrey L. Neyhart, Devin A. Rippner   +7 more
wiley   +1 more source

Hyperspectral imaging for intraoperative brain tumor identification through fusion of spectral, textural, and spectral index features. [PDF]

PLoS One
Liu J, Zhang C, Xu J, Wang L, Pan M, Ma X, Xia W.   +6 more
europepmc   +1 more source

Affordable Phenomics special topic—Foreword for The Plant Phenome Journal

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract The Affordable Phenomics special topic in The Plant Phenome Journal showcased recent advances that expand the accessibility, cost‐effectiveness, and scalability of plant phenotyping technologies. This collection of 15 articles presented innovative approaches, ranging from low‐cost sensors and open‐source analytical pipelines to artificial ...
Valerio Hoyos‐Villegas, Michael A. Gore   +1 more
wiley   +1 more source

Early Detection and Classification of Gibberella Zeae Contamination in Maize Kernels Using SWIR Hyperspectral Imaging and Machine Learning. [PDF]

Sensors (Basel)
Liu K, Li S, Shi W, Guo Z, Shao X, Guo Y, Zhao J, Sun X, Khujamshukurov NA, Du F.   +9 more
europepmc   +1 more source

A highly accurate, low‐cost method for detecting and quantifying soybean leaf flipping phenotype during drought stress

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract A genome‐wide association study (GWAS) using digital images was conducted to delineate regions of the genome that govern the leaf flipping quantitative trait in soybean (Glycine max (L.) Merr). However, converting the digital data to numerical scores for downstream analyses was challenging.
Mohammad Anisur Rahaman, Atit Parajuli, Adnan Hossain Khan, Liang Dong, Madan K Bhattacharyya   +4 more
wiley   +1 more source

Hyperspectral imaging as an objective diagnostic tool for secondary lymphedema in breast cancer patients. [PDF]

Commun Med (Lond)
Weiss M, Jurjuț O, Ehrhardt A, Herholz A, Seller A, Daigeler A, Hahn M, Marx M, Schimunek L, Eisler W.   +9 more
europepmc   +1 more source

Hyperspectral Image Classification

, 2020
Rajesh, Gogineni,, Ashvini, Chaturvedi,
openaire   +3 more sources