Monthly Inter-Lab VIM Meeting Schedule

Please join us Friday, 04/19/2024 11AM ET, for a talk titled “Practical improvements to image sharing workflows in Minerva”. A free and open-source tool, Minerva, has long been in use to render static single-page websites that share scientific images with collaborators and the public. New priorities have emerged from a growing number of users: embedding sample-specific metadata, generating similar pages for many samples, and exporting all channels with semi-automated contrast settings. New workflows and processes to address these needs emerged from a collaborative effort led by the data management and informatics teams at the LSP.

Please join us Friday, 03/08/2024 11AM ET, for a talk titled “Samui Browser - Performant Web-Based Interactive Visualization Tool for Spatially-Resolved Transcriptomics Experiments”. Samui lets the user rapidly and smoothly visualizes their images anywhere without any need for them to download any software or even the images themselves. Samui achieves this without any use of a backend server, relying only on a static cloud storage. It also supports image annotations, which are exportable in the GeoJSON for fast sharing.

Please join us Friday, 02/09/2024 11AM ET, for a talk titled “Under the hood of the HTAN DCC”. The Human Tumor Atlas Network Data Coordinating Center provides the tools, resources and expertise to enable HTAN data contributors to annotate and share their multiplexed tissue imaging and advanced sequencing data according to FAIR principles. In this talk, Adam Taylor, Senior Scientist at Sage Bionetworks, will take you under the hood of the HTAN DCC to look at some of its infrastructure and operations; exposing the challenges of curating and sharing thousands of datasets and millions of metadata attributes across ten research programs.

Please join us Friday, 12/08/2023 11AM ET for a talk titled “Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering”. We present a hybrid multi-volume rendering approach based on a novel Residency Octree that combines the advantages of out-of-core volume rendering using page tables with those of standard octrees. Octree approaches work by performing hierarchical tree traversal. However, in octree volume rendering, tree traversal and the selection of data resolution are intrinsically coupled. This makes fine-grained empty-space skipping costly. Page tables, on the other hand, allow access to any cached brick from any resolution. However, they do not offer a clear and efficient strategy for substituting missing high-resolution data with lower-resolution data. We enable flexible mixed-resolution out-of-core multi-volume rendering by decoupling the cache residency of multi-resolution data from a resolution-independent spatial subdivision determined by the tree. Instead of one-to-one node-to-brick correspondences, each residency octree node is mapped to a set of bricks from different resolution levels. This makes it possible to efficiently and adaptively choose and mix resolutions, adapt sampling rates, and compensate for cache misses. At the same time, residency octrees support fine-grained empty-space skipping, independent of the data subdivision used for caching. Finally, to facilitate collaboration and outreach, and to eliminate local data storage, our implementation is a web-based, pure client-side renderer using WebGPU and WebAssembly. Our method is faster than prior approaches and efficient for many data channels with a flexible and adaptive choice of data resolution.

Please join us Friday, 11/17/2023 11AM ET for a talk titled “Towards a thick-tissue 3D atlas for characterizing cell neighborhoods and shape in melanoma with CyCIF”. Microscopy-based tissue imaging is commonly performed at a resolution sufficient to determine cell types but not detect the subtle morphological features associated with cytoskeletal reorganisation, juxtracrine signalling, or membrane trafficking. Here we introduce a 3D imaging approach with high-resolution 54-plex cyclic immunofluorescence (CyCIF) using existing instruments and reagents that is able to characterize a wide variety of organelles and structures at sub-micron scale, cell morphology at the cellular level, while simultaneously quantifying millimetre-scale spatial features.

Please join us Friday, 10/13/2023 11AM ET for a talk titled “SpatialData: an open and universal data framework for spatial omics”. Spatially resolved omics technologies are transforming our understanding of biological tissues. However, handling uni- and multi-modal spatial omics datasets remains a challenge owing to large volumes of data, heterogeneous data types and the lack of unified spatially-aware data structures. Here, we introduce SpatialData, a framework that establishes a unified and extensible multi-platform file-format, lazy representation of larger-than-memory data, transformations, and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated via multiple vignettes, including integrative analysis on a multi-modal Xenium and Visium breast cancer study.

Please join us Friday, 09/15/2023 11AM ET for a talk titled “The Imaging Data Commons as a platform for reproducible reasearch in digital pathology”. When developing machine learning (ML)-based solutions in computational pathology one of the often underestimated but major challenges is to ensure their reproducibilty. The National Cancer Institute (NCI) Imaging Data Commons (IDC) is a new cloud-based repository within the US national Cancer Research Data Commons (CRDC), which provides more than 120 cancer image collections according to the FAIR principles and is designed to be used with cloud ML services. In our work, we investigated how the IDC and cloud ML services can be used in combination to facilitate reproducibility in computational pathology research. For this purpose we developed a use case, in which we trained and applied a tissue classification model to distinguish between healthy tissue and two different tumor subtypes. We used different datasets from the IDC and implemented our experiments using Google Colaboratory and Google Vertex AI Notebooks. This talk will be about our experiences with setting up a reproducible computational pathology pipeline and summarize some of our pitfalls and learnings.

Please join us Friday, 07/14/2023 11AM ET for a talk titled “VR, data storytelling, AI: more than a fad for visual analytics of hi-plex imaging data?”. Can virtual reality (VR) and data storytelling enrich visual analytics of highly multiplex microscopic imaging data? With NCI SBIR funding aimed at supporting NCI atlas building projects such as HTAN and HubMAP, Quantitative Imaging Systems, Flow Immersive, and OHSU piloted extensions to our QiTissue multiplex visual analytics and Flow’s XR, data storytelling, and AI platforms to explore.

Please join us Friday, 06/16/2023 11AM ET for two talk titled “Computational Segmentation of Renal Microanatomy, and Implication in Diabetes and Transplant “ and “Interactive Visualization of Kidney Structural Segmentations and Associated Pathomic Features on Whole Slide Images”. In this talk, we will introduce computational renal pathology, and discuss detection, segmentation, quantification, and classification of microanatomical structures from renal histology giga-pixel size whole slide images. We will also discuss our ongoing efforts on computational data fusion integrating imaging morphometric and molecular omics data. We will conclude by discussing potential implications of our tools in the area of diabetes and renal transplantation.

Please join us Friday, 05/19/2023 11AM ET for a talk titled “WebAtlas pipeline for integrated single cell and spatial transcriptomic data”. Single cell and spatial transcriptomics illuminate complementary features of tissues. However, online dissemination and exploration of integrated datasets is challenging due to the heterogeneity and scale of data. We introduce the WebAtlas pipeline for user-friendly sharing and interactive navigation of integrated datasets. WebAtlas unifies commonly used atlassing technologies into the cloud-optimised Zarr format and builds on Vitessce to enable remote data navigation. We showcase WebAtlas on the developing human lower limb to cross-query cell types and genes across single cell, sequencing- and imaging-based spatial transcriptomic data.

Please join us Friday, 04/21/2023 11AM ET for a talk titled “Education and Training for Visualization Tools” followed by a discussion on considerations for writing effective software documentation and what community resources would be helpful.

Please join us Friday, 03/10/2023 11AM ET for a talk titled “Scrollytelling in medical communication”.

Please join us Friday, 02/10/2023 11AM ET for a talk about the imaging format OME-NGFF with the title “Report on Status and Roadmap Concerns for OME-NGFF”

Please join us Friday, 01/13/2023 11AM ET for an invited talk and discussion: “Loon. Using Exemplars to Visualize Large-Scale Microscopy Data”. Which drug is most promising for a cancer patient? A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to answer this question in only a few hours. However, the analysis pipeline for extracting data from these images is still far from complete automation: human intervention is necessary for quality control for preprocessing steps such as segmentation, adjusting filters, removing noise, and analyzing the result. To address this workflow, we developed Loon, a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging. Loon visualizes both derived data such as growth rates and imaging data. Since the images are collected automatically at a large scale, manual inspection of images and segmentations is infeasible. However, reviewing representative samples of cells is essential, both for quality control and for data analysis. We introduce a new approach for choosing and visualizing representative exemplar cells that retain a close connection to the low-level data. By tightly integrating the derived data visualization capabilities with the novel exemplar visualization and providing selection and filtering capabilities, Loon is well suited for making decisions about which drugs are suitable for a specific patient.

Please join us Friday, 10/14/2022 11AM ET for two spatial analysis talks. The first talk will be titled “Visinity: Visual Spatial Neighborhood Analysis for Multiplexed Tissue Imaging Data” and focuses on an visual analytics application. The second talk will focus on “Human-Machine Collaboration on the Quantitative Spatial Characterization of Tumor Infiltrating Lymphocytes”

Please join us Friday, 04/08/2022 11AM ET for a categorizing talk and intertwined discussion about “Connecting Pipeline Outputs to Viewer Inputs”.

Please join us Friday, 04/08/2022 11AM ET for a categorizing talk and intertwined discussion about “MITI: Minimum Information Guidelines for Highly Multiplexed Tissue Images”.

Please join us Friday, 04/08/2022 11AM ET for a categorizing talks and intertwined discussions about “Viewers for Multiplexed 3D Imaging Data”. We will have 4 short talks: 3D Imaging and Commercial Viewers - 3D Capabilities of Viv - Neuroglancer and Agave - 3D Slicer.

Please join us Friday, 04/08/2022 11AM ET for a categorizing talk and intertwined discussion about “Multiplexed Image Viewers”.

Please join us Friday, 03/11/2022 11AM ET for a presentation and intertwined discussion about “Image Rendering: Perceptual and Technical tIssues”.

Please join us Friday, 01/14/2022 11AM ET for a presentation and intertwined discussion about “NCI Imaging Data Commons: Approach, status, related tools”.

Today’s talk will be titled: “Minerva - Multiplexed Tissue Visualization for Interactive Data Stories and Data Analysis”. Please join us on Friday 11/22/21 at 11 AM ET via Zoom.

Today’s talk will be given by the Swedlow Lab. Title: “OME’s and Glencoe’s work on NGFF file formats”. Please join us on Friday 10/28/21 at 11 AM ET via Zoom.