Pathology services

Karolinska Institutet (KI)

## Overview This service supports SMEs and researchers in developing, training, and validating AI models for medical imaging applications. Hosted at SMAILE, Karolinska Institutet, it covers segmentation, detection, and classification tasks using CT, MRI, nuclear images, multimodal images, ultrasound, histology, and microscopic images. The pipeline includes data curation, evaluation of labeling strategy, model selection and training, evaluation metric selection, and model performance benchmarking. We provide expertise and support in: - AI model training and optimization for medical imaging - Validation using clinical datasets and standard metrics (using publicly available datasets, datasets available through data agreements, and internal datasets at KI, depending on the case) - Clinical Relevance and Comparison with the state of the art in research and clinical practice - Imaging biomarkers studies for diagnosis, prognosis, and prediction applications ### How can the service help you? The service ensures your imaging AI model performs reliably and is aligned with clinical expectations. Whether you’re entering the pre-clinical testing phase or seeking validation to secure investment or regulatory approval, this service equips you with a rigorous evaluation and feedback report. ### How the service will be delivered? Available both virtually and physically. Imaging data can be reviewed remotely through a secure data transfer process. On-site collaboration is also possible for sensitive datasets or model development, evaluation, and validation. A typical project takes 4–6 weeks. --- ## Additional information ### Provider description SMAILE is the digital health core facility at Karolinska Institute. It offers interdisciplinary support in AI for medical imaging, data analytics, and system validation, partnering with leading institutions under the Swedish TEF-Health node. ### Technical description The imaging model pipeline is extensively validated by using a curated benchmark set and standard evaluation frameworks such as well-established quantification metrics for object detection, image segmentation, and classification tasks.. Annotation quality is reviewed, and model performance is benchmarked against open or reference models. Standard medical image processing tools such as PyDicom, ANTs, and ITK, as well as community-driven open-sourced frameworks such as MONAI, are the core components of our designed pipelines. ### Service customization The service can focus on either model development, evaluation, or both. Datasets can be anonymized and securely shared, or analysis can be conducted in a local sandboxed environment.

Centre Hospitalier Universitaire De Rennes (CHU RENNES)

Anatomic pathology slides: preparation +/- associated patient clinical data +/- analysis +/- software evaluation +/- medical expertise; cancer, lesion, sample, biopsy, tissue, organ; histology, diagnosis, genetic; microscope, scanner

Univerzitna Nemocnica Martin (University Hospital Martin)

This service provides tailored datasets for evaluating AI performance in key medical specialties, including sleep disorder diagnostics, gastroenterology, digital pathology, and radiology. The datasets reflect real clinical scenarios, supporting the validation of AI algorithms and assisting organizations in achieving regulatory compliance and clinical reliability. Each dataset includes structured data and annotations designed for training, testing, and comparing AI models in various clinical contexts. Keywords: AI dataset, clinical diagnostics, digital pathology, radiology, gastroenterology, sleep disorders, performance validation.

Univerzitna Nemocnica Martin (University Hospital Martin)

The service provides testing datasets from whole slide imaging for development of AI-based diagnostic assistance tools. Medical professionals evaluate results obtained by using developed tools to assist diagnostic procedures and tests.

Karolinska Institutet (KI)

The Unit: Clinical Genomics Stockholm (https://www.scilifelab.se/units/clinical-genomics-stockholm/) This infrastructure is part of Science for Life Laboratory (SciLifeLab) which is an academic collaboration between Swedish universities (including Karolinska Institutet) and a national research infrastructure with a focus on life science. Clinical Genomics Stockholm unit is a research infrastructure for large-scale, genomics-based analyses using next generation sequencing technologies. The unit assists in translational research projects, in the translation of genomics-based tools to routine clinical care and also aims to improve the capability for national microbial surveillance and for pandemic preparedness. The Service: Non-human genome sequencing Sequencing of bacterial or viral whole genomes with the possibility of sequence analysis and strain typing. Sequencing of SARS-CoV-2 amplicons. Sequencing of metagenome samples (with PCR-free protocol). This service encompasses: o Consultation (Project design, Target capture design) o Sample management o DNA& RNA sequencing (microbial genomes, metagenomics) o Bioinformatics (Bioinformatic analysis on data generated at CG) Equipment Our unit has access to specialized equipment that enable us to factilitate the translation of new high-throughput techniques into clinical use. These include, but are not restricted to: • Various automatic robotic systems (BRAVO NGS Workstation, Hamilton NGS Star) • Various systems for QC, quantification and fragment analyses (TapeStation, Quantification using fluorescent assay (Qubit, Quantit)) • Instrumentation for real time PCR and ddPCR (BioRad qPCR) • Instrumentation for Multispectral imaging (Saphyr optical mapper) • Sequencing platforms: o Illumina (NovaSeq 6000, NovaSeq 6000 Dx, NovaSeq X) o Nanopore (PromethION “access via NGI”) o PacBio (Revio)

Karolinska Institutet (KI)

The Unit: Clinical Genomics Stockholm (https://www.scilifelab.se/units/clinical-genomics-stockholm/) This infrastructure is part of Science for Life Laboratory (SciLifeLab) which is an academic collaboration between Swedish universities (including Karolinska Institutet) and a national research infrastructure with a focus on life science. Clinical Genomics Stockholm unit is a research infrastructure for large-scale, genomics-based analyses using next generation sequencing technologies. The unit assists in translational research projects, in the translation of genomics-based tools to routine clinical care and also aims to improve the capability for national microbial surveillance and for pandemic preparedness. The Service: Transcriptome sequencing (RNA-seq) Sequencing of mRNA (poly A based method) followed by fusion detection or germline analysis. This service encompasses: o Consultation (Project design, Target capture design) o Sample management o RNA sequencing (total RNA, mRNA) o Bioinformatics (Bioinformatic analysis on data generated at CG) Equipment Our unit has access to specialized equipment that enable us to factilitate the translation of new high-throughput techniques into clinical use. These include, but are not restricted to: • Various automatic robotic systems (BRAVO NGS Workstation, Hamilton NGS Star) • Various systems for QC, quantification and fragment analyses (TapeStation, Quantification using fluorescent assay (Qubit, Quantit)) • Instrumentation for real time PCR and ddPCR (BioRad qPCR) • Instrumentation for Multispectral imaging (Saphyr optical mapper) • Sequencing platforms: o Illumina (NovaSeq 6000, NovaSeq 6000 Dx, NovaSeq X) o Nanopore (PromethION “access via NGI”) o PacBio (Revio)

Karolinska Institutet (KI)

The Unit: Clinical Genomics Stockholm (https://www.scilifelab.se/units/clinical-genomics-stockholm/) This infrastructure is part of Science for Life Laboratory (SciLifeLab) which is an academic collaboration between Swedish universities (including Karolinska Institutet) and a national research infrastructure with a focus on life science. Clinical Genomics Stockholm unit is a research infrastructure for large-scale, genomics-based analyses using next generation sequencing technologies. The unit assists in translational research projects, in the translation of genomics-based tools to routine clinical care and also aims to improve the capability for national microbial surveillance and for pandemic preparedness. The Service: Whole genome or targeted DNA sequencing Sequencing of the entire human genome (with a PCR-free protocol) or selected parts of the genome (through exome or panel sequencing), followed by germline or somatic analysis. This service encompasses: o Consultation (Project design, Target capture design) o Sample management o DNA sequencing (Whole Genome Seq (WGS), Whole Exome Seq (WES), Panels) o Bioinformatics (Bioinformatic analysis (data generated at CG) Equipment: Our unit has access to specialized equipment that enable us to factilitate the translation of new high-throughput techniques into clinical use. These include, but are not restricted to: • Various automatic robotic systems (BRAVO NGS Workstation, Hamilton NGS Star) • Various systems for QC, quantification and fragment analyses (TapeStation, Quantification using fluorescent assay (Qubit, Quantit)) • Instrumentation for real time PCR and ddPCR (BioRad qPCR) • Instrumentation for Multispectral imaging (Saphyr optical mapper) • Sequencing platforms: o Illumina (NovaSeq 6000, NovaSeq 6000 Dx, NovaSeq X) o Nanopore (PromethION “access via NGI”) o PacBio (Revio) Prospective Use case: AI based software solution uses WGS data to identify genetic biomarkers to help clinicians either during diagnostic phase and/or at the treatment phase in order to identify genetic aberrations possibly explaining the disease onset or to assist in the therapeutic decisions such as for example in breast cancer the presence of BRCA1 mutation. AI software can be trained to learn to deliver diagnostic based on WGS data (especially needed in the field of rare diseases) to recognize genetic variations (from single nucleotide to over 50bp deletion or insertion) in a more robust and accurate manner (to limit generation of false negative or false positive cases) to support clinicians in their decision process.