相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Image segmentation evaluation: a survey of methods
Zhaobin Wang et al.
ARTIFICIAL INTELLIGENCE REVIEW (2020)
Single-cell network biology for resolving cellular heterogeneity in human diseases
Junha Cha et al.
EXPERIMENTAL AND MOLECULAR MEDICINE (2020)
Evaluating Cell Metabolism Through Autofluorescence Imaging of NAD(P)H and FAD
Olivia I. Kolenc et al.
ANTIOXIDANTS & REDOX SIGNALING (2019)
Automated Segmentation of Fluorescence Microscopy Images for 3D Cell Detection in human- derived Cardiospheres
Massimo Salvi et al.
SCIENTIFIC REPORTS (2019)
Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids
Joe T. Sharick et al.
NEOPLASIA (2019)
Split and merge watershed: A two-step method for cell segmentation in fluorescence microscopy images
Margarita Gamarra et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2019)
Quantitative Spatial Analysis of Metabolic Heterogeneity Across in vivo and in vitro Tumor Models
Tiffany M. Heaster et al.
FRONTIERS IN ONCOLOGY (2019)
Tumour heterogeneity and resistance to cancer therapies
Ibiayi Dagogo-Jack et al.
NATURE REVIEWS CLINICAL ONCOLOGY (2018)
Segmented cell analyses to measure redox states of autofluorescent NAD(P)H, FAD & Trp in cancer cells by FLIM
Horst Wallrabe et al.
SCIENTIFIC REPORTS (2018)
A deep learning-based algorithm for 2-D cell segmentation in microscopy images
Yousef Al-Kofahi et al.
BMC BIOINFORMATICS (2018)
Local and global evaluation for remote sensing image segmentation
Tengfei Su et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2017)
Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images
Daniel M. Spagnolo et al.
CANCER RESEARCH (2017)
Label-free identification of macrophage phenotype by fluorescence lifetime imaging microscopy
Alba Alfonso-Garcia et al.
JOURNAL OF BIOMEDICAL OPTICS (2016)
Segmentation quality evaluation using region-based precision and recall measures for remote sensing images
Xueliang Zhang et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2015)
Optical metabolic imaging quantifies heterogeneous cell populations
Alex J. Walsh et al.
BIOMEDICAL OPTICS EXPRESS (2015)
In Vivo Autofluorescence Imaging of Tumor Heterogeneity in Response to Treatment
Amy T. Shah et al.
NEOPLASIA (2015)
Optical Imaging of Drug-Induced Metabolism Changes in Murine and Human Pancreatic Cancer Organoids Reveals Heterogeneous Drug Response
Alex J. Walsh et al.
PANCREAS (2015)
Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification
Zhihong Hu et al.
JOURNAL OF MEDICAL IMAGING (2015)
Quantitative Optical Imaging of Primary Tumor Organoid Metabolism Predicts Drug Response in Breast Cancer
Alex J. Walsh et al.
CANCER RESEARCH (2014)
Optical Metabolic Imaging Identifies Glycolytic Levels, Subtypes, and Early-Treatment Response in Breast Cancer
Alex J. Walsh et al.
CANCER RESEARCH (2013)
Automatic Segmentation of Eight Tissue Classes in Neonatal Brain MRI
Petronella Anbeek et al.
PLOS ONE (2013)
Optical Imaging Using Endogenous Contrast to Assess Metabolic State
Irene Georgakoudi et al.
ANNUAL REVIEW OF BIOMEDICAL ENGINEERING, VOL 14 (2012)
Western Blot: Technique, Theory, and Trouble Shooting
Tahrin Mahmood et al.
NORTH AMERICAN JOURNAL OF MEDICAL SCIENCES (2012)
Tumor heterogeneity: Causes and consequences
Andriy Marusyk et al.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER (2010)
Performance measure characterization for evaluating neuroimage segmentation algorithms
Herng-Hua Chang et al.
NEUROIMAGE (2009)
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Anne E. Carpenter et al.
GENOME BIOLOGY (2006)
What can cell biology tell us about heterogeneity in lysosomal storage diseases?
V Gieselmann
ACTA PAEDIATRICA (2005)