[go: up one dir, main page]

Mantes et al., 2024 - Google Patents

Spotiflow: accurate and efficient spot detection for imaging-based spatial transcriptomics with stereographic flow regression. biorxiv

Mantes et al., 2024

View PDF
Document ID
1034466073867890322
Author
Mantes A
Herrera A
Khven I
Schlaeppi A
Kyriacou E
Tsissios G
Aztekin C
Lingner J
La Manno G
Weigert M
Publication year
Publication venue
Published online January

External Links

Snippet

Many methods in the life sciences generate images in which the detection and localization of spot-like objects is a crucial first analysis step for more complex downstream tasks, a problem commonly referred to as spot detection [1–4]. While spot detection has been the …
Continue reading at scholar.archive.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30024Cell structures in vitro; Tissue sections in vitro
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/0014Pre-processing, e.g. image segmentation ; Feature extraction
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/00147Matching; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10Investigating individual particles
    • G01N15/14Electro-optical investigation, e.g. flow cytometers

Similar Documents

Publication Publication Date Title
Gritti et al. MOrgAna: accessible quantitative analysis of organoids with machine learning
US20240257914A1 (en) Method and system for 3d reconstruction of tissue gene expression data
Stegmaier et al. Real-time three-dimensional cell segmentation in large-scale microscopy data of developing embryos
Bajcsy et al. Survey statistics of automated segmentations applied to optical imaging of mammalian cells
Kachouie et al. Probabilistic model‐based cell tracking
Jug et al. Bioimage informatics in the context of Drosophila research
Fishman et al. Practical segmentation of nuclei in brightfield cell images with neural networks trained on fluorescently labelled samples
Dominguez Mantes et al. Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression
Aaron et al. Practical considerations in particle and object tracking and analysis
Mantes et al. Spotiflow: accurate and efficient spot detection for imaging-based spatial transcriptomics with stereographic flow regression. biorxiv
Ersoy et al. Segmentation and classification of cell cycle phases in fluorescence imaging
Wang et al. Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering
Murphy et al. Self-supervised learning of cell type specificity from immunohistochemical images
Wang Cross-domain microscopy cell counting by disentangled transfer learning
Li et al. Detection and tracking of overlapping cell nuclei for large scale mitosis analyses
Gertych et al. Automated quantification of DNA demethylation effects in cells via 3D mapping of nuclear signatures and population homogeneity assessment
Tymchenko et al. Classifying mixed patterns of proteins in microscopic images with deep neural networks
Leger et al. Sequence models for continuous cell cycle stage prediction from brightfield images
Liimatainen et al. Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks
Fishman et al. Segmenting nuclei in brightfield images with neural networks
CN111534563B (en) A method and system for evaluating cellular immunotherapy
Gautam et al. Deep learning based method for segmentation, tracking, and analysis of intracellular proteins and their interactions
Severins et al. Point set registration for combining fluorescence microscopy methods
DURO et al. Deep learning-based detection, segmentation and average area estimation of cells
Quachtran et al. Voting-based segmentation of overlapping nuclei in clarity images