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Scope2Screen is an open-source web-application for Multiplexed Image Exploration and Annotation with a python Flask backend and a Node.js javascript frontend. The server’s restful API allows to retrieve image and feature data and to steer analytics. The frontend is built using Bootstrap, D3.js, and openseadragon, a web-based zoomable imageviewer, which we extend significantly.

image The extension offers (A) Channel & color selection for multi-channel rendering. (B) A WebGL-based viewer capable of rendering 100+GB sized high-plexed and high-resolution (≥30k×30k) image data in real-time. (C) Interactive lensing forclose-up analysis - the lens shows a multi-channel immune setting that is different from the global context highlighting basic tissue composition. (D) Dotter panel - stores and organizes snapshots of annotated ROIs to filter, restore, navigate to the image location.

The code is available here:

Scope2Screen implements and customizes a lens tooling that we developed as 'OpenSeaDragon pluging'.

Installation

For End Users

Download latest release and execute it. This will start a local server on your machine. Open the browser and navigate to: http://mts-lsp-l06208:8000/

For Developers

  1. Clone locally from Github: git clone [email protected]:labsyspharm/scope2screen.git
  2. Run from readme.md (no new env updates)

Functionality

Magnifiers

Different settings can be used to magnify the lens area.

To magnify press "." to zoom out press ",". To switch the magifier press "m".

Standard | Fisheye | Plateau

The lens shape can be changed by pressing "⇧ l".

Image Filters

The lens offers different image filters. To switch the feature press: Previous lens: "⇧ [" // Next lens: "⇧ ]"

Generic: Grayscale | Invert | Threshold | Gamma | Context-adaptive: Sobel Edge

Image Channel Filters

The lens offers different image channel filters. To switch the feature press: Previous lens: "⇧ [" // Next lens: "⇧ ]"

Generic: Single Channel| Multi-Channel | Splitscreen

Single-Cell Features

The lens offers different single-cell features, linking extracted single-cell statistics with the image space. To switch the feature press: Previous lens: "⇧ [" // Next lens: "⇧ ]"

Data-driven: Segmentation Mask | Cell Types | Single Cell istribution - Histograms | Single Cell Means - Radial

Snapshots and Annotations

For a region of innterest (ROI) a snapshots can be taken by pressing "⇧ d". The taken snapshot then appears in the Dotter panel on the right side of the tool.

image

The rich snapshot and annotation process. (A) During close-up analysis, the user focuses on an ROI and takes a snapshot. (B) The snapshot is annotated with title and description and saved to a database. (C) The Dotter panel links snapshots to the image space (left). Lens-settings such as channel combination and colors are preserved. (D) Annotated regions can be reactivated as lenses to explore further or fine-tune.

Publication

Jessup J, Krueger R, Warchol S, Hoffer J, Muhlich J, Ritch CC, Gaglia G, Coy S, Chen YA, Lin JR, Santagata S, Sorger PK, Pfister H. Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data. IEEE Transaction on Visualization and Computer Graphics. 2021 Oct 4; doi: 10.1109/TVCG.2021.3114786. Epub ahead of print. PMID: 34606456