Carolina Wählby
Professor at Department of Information Technology; Vi3; Image Analysis
- Telephone:
- +46 18 471 34 73
- E-mail:
- carolina.wahlby@it.uu.se
- Visiting address:
- Hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
More information is available to staff who log in.
Short presentation
I'm a professor in quantitative microscopy at the Dept. of Information Technology and SciLifeLab. My research group is focused on developing computational image analysis approaches based on AI and deep learning for extracting information from microscopy images. Images typically come from experiments aimed to understand biology or diagnose disease, and projects range from large-scale cell-based screens for drug development to in situ RNA sequencing, see more at my lab web page.
Keywords
- algorithms
- artificial intelligence
- bildanalys
- datoriserad bildanalys
- deep learning
- digital pathology
- digital patologi
- electron microscopy
- fluorescence microscopy
- free and open source software
- image analysis
- informationsteknologi
- life science
- light microscopy
- quantitative methods
- scilifelab
Biography
I received a MSc in Molecular Biothechnology in 1998, and during my MSc thesis work at the Karolinska Institute I was fascinated by how cells can be studied using microscopy, and continued as a PhD student in digital image processing at Uppsala University, focusing on methods for finding cells and extracting quantitative measurements from digital microscopy data. After completeing my PhD in 2003, I did a postdoc in genetics and pathology, with emphasis on methods development. I joined the Broad Institute of Harvard and MIT i USA in 2009, and worked with algorithms for analysis of large scale experiments on model organisms such as C. elegans worms and zebrafish to evaluate the effect of new potential drugs. I returned to Sweden and SciLifeLab and became full professor in quantitative microscopy at the centre for image analysis, Dept. of Information Technology, in 2014. My reserach group develops digital image processing and analysis methods for analysis of different types of microscopy image data with applications in the life sciences and medicine, both basic and more application oriented research.
More information is available on my lab web page.
Research
Digital image processing and analysis is all about interpreting image data using a computer. As an example, we can train a computer to recognize different family members from our holiday photos or automatically decipher the license plate of a car at a car toll. My research group develops digital image analysis methods for automated analysis and extraction of quantitative information from digital image data collected via different types of microscopy. The goal of the analysis is often to measure changes in color, shape, pattern or size from large numbers of images collected by automated microscopy systems, for example to evaluate how different drugs affect cells or model organisms in a laboratory environment. We also quantify morphological changes in tissue samples, using deep convolutional neural networks (a branch of AI, artificial intelligence) aiming to diagnose disease or better understand how the body responds to different treatments. We collaborate with researchers from the life sciences and medicine, and develop methods that can answer important questions in a robust, fast, and reproducible way.
More information can be found on my lab web page.
Publications
Selection of publications
- Deep Learning in Image Cytometry (2019)
- Automated training of deep convolutional neural networks for cell segmentation (2017)
- In situ sequencing for RNA analysis in preserved tissue and cells (2013)
- An image analysis toolbox for high-throughput C. elegans assays (2012)
- In situ detection of phosphorylated platelet-derived growth factor receptor beta using a generalized proximity ligation method (2007)
- Combining intensity, edge, and shape information for 2D and 3D segmentation of cell nuclei in tissue sections (2004)
Recent publications
- Points2Regions (2024)
- Spatial Transcriptome Mapping of the Desmoplastic Growth Pattern of Colorectal Liver Metastases by In Situ Sequencing Reveals a Biologically Relevant Zonation of the Desmoplastic Rim (2024)
- DEPICTER (2024)
- Learned morphological features guide cell type assignment of deconvolved spatial transcriptomics (2024)
- Self-Supervised Learning for Genetically Relevant Domain Identification in Morphological Images (2024)
All publications
Articles
- Points2Regions (2024)
- Spatial Transcriptome Mapping of the Desmoplastic Growth Pattern of Colorectal Liver Metastases by In Situ Sequencing Reveals a Biologically Relevant Zonation of the Desmoplastic Rim (2024)
- DEPICTER (2024)
- PACMan (2024)
- Visualization and quality control tools for large-scale multiplex tissue analysis in TissUUmaps3 (2023)
- Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy (2023)
- Evaluating the utility of brightfield image data for mechanism of action prediction (2023)
- TissUUmaps 3 (2023)
- A topographic atlas defines developmental origins of cell heterogeneity in the human embryonic lung (2023)
- Spatial Statistics for Understanding Tissue Organization (2022)
- Automated detection of vascular remodeling in human tumor draining lymph nodes by the deep learning tool HEV-finder (2022)
- Regular Use of Depot Medroxyprogesterone Acetate Causes Thinning of the Superficial Lining and Apical Distribution of Human Immunodeficiency Virus Target Cells in the Human Ectocervix (2022)
- SimSearch (2022)
- De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks (2022)
- Improved breast cancer histological grading using deep learning (2022)
- Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit (2021)
- Morphological Features Extracted by AI Associated with Spatial Transcriptomics in Prostate Cancer (2021)
- ImageJ and CellProfiler (2021)
- Deep-learning models for lipid nanoparticle-based drug delivery (2021)
- Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps (2021)
- Genes in human obesity loci are causal obesity genes in C. elegans (2021)
- Spage2vec (2021)
- Comparison of East‐Asia and West‐Europe cohorts explains disparities in survival outcomes and highlights predictive biomarkers of early gastric cancer aggressiveness (2021)
- Towards automatic protein co-expression quantification in immunohistochemical TMA slides (2021)
- Machine learning for cell classification and neighborhood analysis in glioma tissue (2021)
- Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images (2021)
- TEM image restoration from fast image streams (2021)
- Automated identification of the mouse brain’s spatial compartments from in situ sequencing data (2020)
- Introducing Hann windows for reducing edge-effects in patch-based image segmentation (2020)
- TissUUmaps (2020)
- Artificial intelligence for diagnosis and grading of prostate cancer in biopsies (2020)
- Deep Learning in Image Cytometry (2019)
- Impact of Q-Griffithsin anti-HIV microbicide gel in non-human primates (2019)
- The Effect of DMPA Use on the Human Cervical Epithelium (2018)
- Human Immunodeficiency Virus-Infected Women Have High Numbers of CD103-CD8+ T Cells Residing Close to the Basal Membrane of the Ectocervical Epithelium (2018)
- Multiplexed fluorescence microscopy reveals heterogeneity among stromal cells in mouse bone marrow sections (2018)
- Image-Based Detection of Patient-Specific Drug-Induced Cell-Cycle Effects in Glioblastoma (2018)
- Quantitative image analysis of protein expression and colocalisation in skin sections (2018)
- Quantitative high-content/high-throughput microscopy analysis of lipid droplets in subject-specific adipogenesis models (2017)
- A comprehensive structural, biochemical and biological profiling of the human NUDIX hydrolase family (2017)
- Hormonal contraceptive use affects HIV susceptibility (2017)
- Increased numbers of CD103-CD8+ TRM cells in the cervical mucosa of HIV-infected women (2017)
- Deep Fish (2017)
- Automated training of deep convolutional neural networks for cell segmentation (2017)
- A short feature vector for image matching (2017)
- Bridging Histology and Bioinformatics (2017)
- Differential neuroprotective effects of interleukin-1 receptor antagonist on spinal cord neurons after excitotoxic injury (2017)
- Objective automated quantification of fluorescence signal in histological sections of rat lens (2017)
- Analysis of the distribution of CD103 on CD8 T cells in blood and genital mucosa of HIV-infected female sex workers (2016)
- Segmentation and track-analysis in time-lapse imaging of bacteria (2016)
- PopulationProfiler (2016)
- Global Gray-level Thresholding Based on Object Size (2016)
- Automatic quantification of fluorescence signal in rat lens epithelium (2016)
- The quest for multiplexed spatially resolved transcriptional profiling (2016)
- Quantitative analysis of immunofluorescence and in situ PLA staining using CellProfiler reveals impaired epidermal lipid processing pathway in ARCI patients with CYP4F22 mutations (2016)
- Compaction of rolling circle amplification products increases signal integrity and signal–to–noise ratio (2015)
- Next-Generation Pathology (2015)
- Automated analysis of dynamic behavior of single cells in picoliter droplets (2014)
- High- and low-throughput scoring of fat mass and body fat distribution in C. elegans (2014)
- Blind Color Decomposition of Histological Images (2013)
- Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas (2013)
- In situ sequencing for RNA analysis in preserved tissue and cells (2013)
- Pseudomonas aeruginosa Disrupts Caenorhabditis elegans Iron Homeostasis, Causing a Hypoxic Response and Death (2013)
- High-throughput hyperdimensional vertebrate phenotyping (2013)
- Fully automated cellular-resolution vertebrate screening platform with parallel animal processing (2012)
- Non-Random mtDNA Segregation Patterns Indicate a Metastable Heteroplasmic Segregation Unit in m.3243A>G Cybrid Cells (2012)
- Visualising individual sequence-specific protein-DNA interactions in situ (2012)
- An image analysis toolbox for high-throughput C. elegans assays (2012)
- Increasing the dynamic range of in situ PLA (2011)
- Automated Classification of Multicolored Rolling Circle Products in Dual-Channel Wide-Field Fluorescence Microscopy (2011)
- Robust signal detection in 3D fluorescence microscopy (2010)
- Bright-Field Microscopy Visualization of Proteins and Protein Complexes by In Situ Proximity Ligation with Peroxidase Detection (2010)
- BlobFinder, a tool for fluorescence microscopy image cytometry (2009)
- Quantification of colocalization and cross-talk based on spectral angles (2009)
- A single molecule array for digital targeted molecular analyses (2009)
- A detailed analysis of 3D subcellular signal localization (2009)
- Finding cells, finding molecules, finding patterns (2008)
- Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis (2007)
- In situ detection of phosphorylated platelet-derived growth factor receptor beta using a generalized proximity ligation method (2007)
- Robust cell image segmentation methods (2004)
- Image Analysis for Automatic Segmentation of Cytoplasms and Classification of Rac1 Activation (2004)
- Combining intensity, edge, and shape information for 2D and 3D segmentation of cell nuclei in tissue sections (2004)
- Abnormal expression pattern of cyclin E in tumour cells (2003)
- Sequential immunofluorescence staining and image analysis for detection of large numbers of antigens in individual cell nuclei (2002)
- A detailed analysis of cyclin A accumulation at the G1/S border in normal and transformed cells. (2000)
- Intracellular distribution of an integral nuclear pore membrane protein fused to green fluorescent protein--localization of a targeting domain (1997)
- ISTDECO
- Spatial transcriptome mapping of the desmoplastic growth pattern of colorectal liver metastases by in situ sequencing reveals a biologically relevant zonation of the desmoplastic rim
- Decoding and spatial analysis of ISS data for understanding the mouse olfactory epithelium organization
- Discovery of tumour indicating morphological changes in benign prostate biopsies through AI
- What makes for good morphology representations for spatial omics?
- Compaction of rolling circle amplification products increases signal strength and integrity
- The tumour microenvironment across tumour evolution in bladder cancer profiled by single-cell RNA-sequencing analysis and spatial transcriptomics
- Identification of spatial compartments in tissue from in situ sequencing data
- Spage2vec: Unsupervised detection of spatial gene expression constellations
- TissUUmaps 3
- Pathologist-Level Grading of Prostate Biospies with Artificial intelligence
- Objective automated quantification of fluorescence signal in histological sections of rat lens
- Continuous imaging of exocytosis in β-cells reveals negative feedback of insulin
Books
Chapters
Conferences
- Learned morphological features guide cell type assignment of deconvolved spatial transcriptomics (2024)
- Self-Supervised Learning for Genetically Relevant Domain Identification in Morphological Images (2024)
- Cell Segmentation of in situ Transcriptomics Data using Signed Graph Partitioning (2023)
- Is brightfield all you need for MoA prediction? (2022)
- Rotationally Equivariant Representation Learning for Multimodal Images (2022)
- Graph-based image decoding for multiplexed in situ RNA detection (2021)
- Contrastive Learning for Equivariant Multimodal Image Representations (2021)
- Comir: Contrastive multimodal image representation for registration (2021)
- Registration of Multimodal Microscopy Images using CoMIR – learned structural image representations (2021)
- Transcriptome-Supervised Classification of Tissue Morphology Using Deep Learning (2020)
- Weakly-supervised prediction of cell migration modes in confocal microscopy images using bayesian deep learning (2020)
- In Silico Prediction of Cell Traction Forces (2020)
- CoMIR: Contrastive Multimodal Image Representation for Registration (2020)
- Detection of Malignancy-Associated Changes Due to Precancerous and Oral Cancer Lesions: A Pilot Study Using Deep Learning (2018)
- Brush Biopsy For HR-HPV Detection With FTA Card And AI For Cytology Analysis - A Viable Non-invasive Alternative (2018)
- Whole Slide Image Registration for the Study of Tumor Heterogeneity (2018)
- Decoding gene expression in 2D and 3D (2017)
- A web application to analyse and visualize digital images at multiple resolutions (2017)
- Spheroid segmentation using multiscale deep adversarial networks (2017)
- Deep convolutional neural networks for detecting cellular changes due to malignancy (2017)
- TissueMaps (2016)
- Feature augmented deep neural networks for segmentation of cells (2016)
- Comparison of Flow Cytometry and Image-Based Screening for Cell Cycle Analysis (2016)
- Global And Local Adaptive Gray-level Thresholding Based on Object Features (2016)
- Fast Adaptive Local Thresholding Based on Ellipse fit (2016)
- Automatic grading of breast cancer from whole slide images of Ki67 stained tissue sections (2016)
- Your New Default Thresholding Method? (2015)
- An Evaluation of the Faster STORM Method for Super-resolution Microscopy (2014)
- The Giga-pixel Challenge: Full Resolution Image Analysis – Without Losing the Big Picture (2014)
- Image-based screening of zebrafish (2013)
- Automated quantification of Zebrafish tail deformation for high-throughput drug screening (2013)
- Light Tomography (2013)
- Large-Scale Analysis of Live Cells (2013)
- Viewing and analyzing slide scanner data using CellProfiler (work in progress) (2013)
- An image based high-throughput assay for chemical screening using zebrafish. (2012)
- Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas (2012)
- Making isotropic 3D imaging at microscopic scale accessible to every lab (2012)
- Isotropic 3D imaging of biological specimens at micro and nano scale (2012)
- Optimization of semi-automated cell tracking using application-expert feed-back (2012)
- High throughput phenotyping of model organisms (2012)
- Approaches for increasing throughput andinformation content of image-based zebrafishscreens (2011)
- High-throughput cellular-resolution in vivo vertebrate screening (2011)
- Signal Detection in 3D by Stable Wave Signal Verification (2009)
- Suppression of Autofluorescence based on Fuzzy Classification by Spectral Angles (2009)
- Spectral Angle Histogram (2009)
- Dimensionality Reduction for Colour Based Pixel Classification (2009)
- Algorithms for cross-talk suppression in fluorescence microscopy (2008)
- Image analysis in fluorescence microscopy (2008)
- Image based measurements of single cell mtDNA mutation load MTD 2007 (2007)
- Image Based Measurements of Single Cell mtDNA Mutation Load (2007)
- Segmentation of Cytoplasms of Cultured Cells (2007)
- Quantification and Localization of Colocalization (2007)
- On color spaces for cytology (2007)
- Finding cells, finding molecules, finding patterns (2006)
- Easy-to-use object selection by color space projections and watershed segmentation (2005)
- Digital image processing for multiplexing of single molecule detection (2005)
- Modeling stem cell migration by Hidden Markov (2004)
- Segmentation of point-like fluorescent markers (2004)
- Time-lapse microscopy and image analysis for tracking stem cell migration (2004)
- Segmentation of cell nuclei in tissue by combining seeded watersheds with gradient information (2003)
- Watershed techniques for segmentation in image cytometry (2003)
- Robust methods for image segmentation and measurements. (2003)
- Detection of large numbers of antigens using sequential immunofluorescence staining (2001)
- Statistical quality control for segmentation of fluorescence labelled cells (2001)
- Analysis of cells using image data from sequential immunofluorescence staining experiments (2001)
- Multiple tissue antigen analysis by sequential immunofluorescence staining and multi-dimensional image analysis (2001)
- Multi-dimensional image analysis of sequential immunofluorescence staining (2001)
- Automatic cytoplasm segmentation of fluorescence labelled cells (2000)