Laboratory Investigation
Publications and presentations
Key publications
INIFY Prostate cancer predictions on biopsies – performance and efficiency study on WSIs from two pathology labs in the US
Poster presentation at Pathology Visions 2022
Read moreEvaluation of 3 different scanners’ performance in creating images suitable for INIFY Prostate to accurately predict suspicious cancer areas in prostate biopsies
Poster presentation Scanner Evaluation, DPA 2021
Read moreDeep neural network as a decision support tool for the detection of lymph node metastases of colorectal cancer
Modern Pathology, February 2023
Read more
Articles
December 2023Evaluation of A Computer Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors
Jennifer Vazzano, Dorota Johansson, Kun Hu, Kristian Eurén, Stefan Elfwing, Anil Parwani, Ming Zhou
Article (link)February 2023A Deep Neural Network–Based Decision Support Tool for the Detection of Lymph Node Metastases in Colorectal Cancer Specimens
Modern PathologyCsaba Kindler, Stefan Elfwing, John Öhrvik, Maziar Nikberg
Article (link)January 2023Predictive uncertainty estimation for out-of-distribution detection in digital pathology
Medical Image AnalysisJasper Linmans, Stefan Elfwing, Jeroen van der Laak, Geert Litjens
Article (link)December 2019Clinical-grade Computational Pathology: Alea Iacta Est
Journal of Pathology InformaticsFilippo Fraggetta
Article (link)August 2018From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge
IEEE Transactions on Medical ImagingPeter Bandi, Oscar Geesink, Ludwig Jacobsson, Martin Hedlund et al.
Article (link)Conferences
2022INIFY Prostate cancer predictions on biopsies – performance and efficiency study on WSIs from two pathology labs in the US
Pathology Visions 2022Jennifer Vazzano, Kun Hu, Dorota Johansson, Kristian Eurén, Stefan Elfwing, Ming Zhou, Anil Parwani
Poster (PDF)2021Evaluation of 3 different scanners’ performance in creating images suitable for INIFY Prostate to accurately predict suspicious cancer areas in prostate biopsies
DPA 2021Anil Parwani, Dorota Johansson, Kristian Eurén, Lena Kajland Wilén, Ming Zhou
Abstract (link)2021Deep neural network as a decision support tool for the detection of lymph node metastases of colorectal cancer
Modern Pathology2020An AI-based tool to identify cancer areas in lung biopsies
ECP 2020Patrick Micke, Lars Björk, Hedvig Elfving, Stefan Elwing, Mats Andersson, Cecilia Lindskog, Lena Kajland Wilen
Poster (PDF)2020Detection of lymph node metastasis in colorectal cancer with the help of deep neural network
ECP 2020Csaba Miklos Kindler, Giorgia Milli, Christel Ottosson, Kristian Euren, Lena Kajland Wilen, Maziar Nikberg
Poster (PDF)2018Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
MIDL 2018, Oral PresentationNikolay Burlutskiy, Nicolas Pinchaud, Feng Gu, Daniel Hägg, Mats Andersson, Lars Björk Kristian Eurén, Cristina Svensson, Lena Kajland Wilén, Martin Hedlund
Abstract (link)2018A Deep Learning Framework for Automatic Diagnosis in Lung Cancer
MIDL 2018Nikolay Burlutskiy, Feng Gu, Lena Kajland Wilen, Max Backman, Patrick Micke
Poster (PDF)2018Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images
MICCAI 2018, COMPAY Workshop on computational pathologyFeng Gu, Nikolay Burlutskiy, Mats Andersson, and Lena Kajland Wilén.
Abstract (link)2018A new high-throughput auto-annotation method to detect and outline cancer areas in prostate biopsies
ECDP 2018, Oral PresentationLars Björk, Jonas Gustafsson, Feria Hikmet Noraddin, Kristian Eurén, Cecilia Lindskog
Abstract (link)2018Determining the scale of image patches using a Deep Learning Approach
ISBI 2018Sebastian Otálora, Oscar Perdomo, Manfredo Atzori, Mats Andersson, Ludwig Jacobsson, Martin Hedlund, Henning Müller
Abstract (link)2018Tumor proliferation grading from whole slide images
SPIE 2018Mikael Rousson, Martin Hedlund, Mats Andersson, Ludwig Jacobsson, Gunnar Lathen, Bjorn Norell, Oscar Jimenez-del-Toro, Henning Mueller, Manfredo Atzori.
Abstract (link)2017Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score
SPIE 2017Oscar Jimenez del Toro, Manfredo Atzori, Sebastian Otálora, Mats Andersson, Kristian Eurén, Martin Hedlund, Peter Rönnquist, Henning Müller
Abstract (link)