# Cell Image Analysis Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/cell-image-analysis-techniques/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers covers advanced techniques and tools in bioimage analysis, microscopy, and high-content screening. It includes topics such as machine learning for cellular image analysis, automated neuronal morphology reconstruction, deep learning applications, and phenotypic profiling of cellular responses. The papers also discuss the use of advanced image processing methods and the integration of high-throughput microscopy in drug discovery. |
| Domain | Life Sciences |
| Field | Biochemistry, Genetics and Molecular Biology |
| OpenAlex ID | t12859 |
| Works | 126 |

## Topic papers all

Showing 15 of 126.

- [Fast, sensitive and accurate integration of single-cell data with Harmony](https://scholariq.org/papers/fast-sensitive-and-accurate-integration-of-single-cell-data-with-harmony/)
- [Determining cell type abundance and expression from bulk tissues with digital cytometry](https://scholariq.org/papers/determining-cell-type-abundance-and-expression-from-bulk-tissues-with-digital/)
- [Spatial registration and normalization of images](https://scholariq.org/papers/spatial-registration-and-normalization-of-images/)
- [Clinical-grade computational pathology using weakly supervised deep learning on whole slide images](https://scholariq.org/papers/clinical-grade-computational-pathology-using-weakly-supervised-deep-learning-on/)
- [Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python](https://scholariq.org/papers/nipype-a-flexible-lightweight-and-extensible-neuroimaging-data-processing/)
- [A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography](https://scholariq.org/papers/a-collaborative-framework-for-3d-alignment-and-classification-of-heterogeneous/)
- [Assessing the significance of focal activations using their spatial extent](https://scholariq.org/papers/assessing-the-significance-of-focal-activations-using-their-spatial-extent/)
- [Single-cell RNA sequencing technologies and bioinformatics pipelines](https://scholariq.org/papers/single-cell-rna-sequencing-technologies-and-bioinformatics-pipelines/)
- [Scientific discovery in the age of artificial intelligence](https://scholariq.org/papers/scientific-discovery-in-the-age-of-artificial-intelligence/)
- [Eleven grand challenges in single-cell data science](https://scholariq.org/papers/eleven-grand-challenges-in-single-cell-data-science/)
- [High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response](https://scholariq.org/papers/high-throughput-screening-using-patient-derived-tumor-xenografts-to-predict/)
- [Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images](https://scholariq.org/papers/spatial-organization-and-molecular-correlation-of-tumor-infiltrating-lymphocytes/)
- [Human–computer collaboration for skin cancer recognition](https://scholariq.org/papers/human-computer-collaboration-for-skin-cancer-recognition/)
- [BigBrain: An Ultrahigh-Resolution 3D Human Brain Model](https://scholariq.org/papers/bigbrain-an-ultrahigh-resolution-3d-human-brain-model/)
- [The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models](https://scholariq.org/papers/the-microarray-quality-control-maqc-ii-study-of-common-practices-for-the/)

## Topic primary papers

Showing 15 of 25.

- [Scientific discovery in the age of artificial intelligence](https://scholariq.org/papers/scientific-discovery-in-the-age-of-artificial-intelligence/)
- [High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response](https://scholariq.org/papers/high-throughput-screening-using-patient-derived-tumor-xenografts-to-predict/)
- [BigBrain: An Ultrahigh-Resolution 3D Human Brain Model](https://scholariq.org/papers/bigbrain-an-ultrahigh-resolution-3d-human-brain-model/)
- [The human body at cellular resolution: the NIH Human Biomolecular Atlas Program](https://scholariq.org/papers/the-human-body-at-cellular-resolution-the-nih-human-biomolecular-atlas-program/)
- [Intelligent Image-Activated Cell Sorting](https://scholariq.org/papers/intelligent-image-activated-cell-sorting/)
- [Morphological diversity of single neurons in molecularly defined cell types](https://scholariq.org/papers/morphological-diversity-of-single-neurons-in-molecularly-defined-cell-types/)
- [A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data](https://scholariq.org/papers/a-mean-three-dimensional-atlas-of-the-human-thalamus-generation-from-multiple/)
- [Recognizing the reagent microbiome](https://scholariq.org/papers/recognizing-the-reagent-microbiome/)
- [Multiscale modeling meets machine learning: What can we learn?](https://scholariq.org/papers/multiscale-modeling-meets-machine-learning-what-can-we-learn/)
- [Automated Segmentation, Classification, and Tracking of Cancer Cell Nuclei in Time-Lapse Microscopy](https://scholariq.org/papers/automated-segmentation-classification-and-tracking-of-cancer-cell-nuclei-in-time/)
- [Robust estimation of bacterial cell count from optical density](https://scholariq.org/papers/robust-estimation-of-bacterial-cell-count-from-optical-density/)
- [A Framework for the Automated Analysis of Subcellular Patterns in Human Protein Atlas Images](https://scholariq.org/papers/a-framework-for-the-automated-analysis-of-subcellular-patterns-in-human-protein/)
- [Semi-automated quantification of axonal densities in labeled CNS tissue](https://scholariq.org/papers/semi-automated-quantification-of-axonal-densities-in-labeled-cns-tissue/)
- [Rapid detection of rice disease using microscopy image identification based on the synergistic judgment of texture and shape features and decision tree–confusion matrix method](https://scholariq.org/papers/rapid-detection-of-rice-disease-using-microscopy-image-identification-based-on/)
- [A novel computational approach for automatic dendrite spines detection in two-photon laser scan microscopy](https://scholariq.org/papers/a-novel-computational-approach-for-automatic-dendrite-spines-detection-in-two/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.