Related services

• AI Imaging Lab: Development & Validation of Segmentation and Detection Models

  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.

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• Anatomic pathology: human prepared slides, data, analysis, expertise

  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

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• Datasets for Diagnostic Evaluation and AI Performance in Medical Specialties

  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.

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• DNA & RNA analysis

  Univerzita Komenskeho V Bratislave (UK BA)

  (1) The laboratory provides microsatellite instability (MSI) in FFPE cancer tissue in low throughput screening methods, including PCR and fragment analysis. The service includes insight into technology, sample preparation, and partial or full bioinformatic data processing in GeneMapper v.6 software. (2) Next, the laboratory provides DNA methylation analysis in promoter regions of genes in low and medium throughput screening methods, including pyrosequencing and/or MS-MLPA and fragment analysis. The service includes insight into technology, sample preparation, and partial or full bioinformatic data processing in Cofalyser.net softvare. (3) The laboratory also provides comparative genomic hybridization (CGH), as well as single nucleotide polymorphism (SNP) detection by microarray that enables identification of aneuploidies, microdeletions, microduplications, as well as other types of chromosomal aberrations across the genome. The service includes insight into technology, sample preparation, and partial or full bioinformatic data processing. (4) The laboratory provides detection of single nucleotide variation from various types of samples by real-time PCR or Sanger sequencing. The method is also usefull for verification of whole genome sequencing results. The service includes insight into technology, sample preparation, and partial or full bioinformatic data processing. (5) The laboratory also provides targeted sequencing of selected parts of the genome (e.g. TruSight Oncology 500 panel), followed by somatic or germline analysis. The service includes insight into technology, sample preparation, and partial or full bioinformatic data processing in Pierian software with clinical interpretation.

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• EUCAIM Platform

  Eucaim

  Cancer Image Europe provides a robust, trustworthy platform for researchers, clinicians, and innovators to access diverse cancer images, enabling the benchmarking, testing, and piloting of AI-driven technologies. EUCAIM Platform integrates a dashboard, a catalogue and a federated searching environment to discover Medical Imaging data related to cancer from a distributed federation of data holders. EUCAIM provides in some nodes processing capacity to securely access the data. EUCAIM is mainly intended for Data scientists to develop, validate or improve AI models or image postprocessing tools. The platform is accessible in https://dashboard.eucaim.cancerimage.eu/

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• Evaluation of AI performance in digital pathology

  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.

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