Patrick Micke, Lars Björk, Hedvig Elfving, Stefan Elwing, Mats Andersson, Cecilia Lindskog, Lena Kajland Wilen
Publications
An AI-based tool to identify cancer areas in lung biopsies
Presentation at ECP 2020, December.
Csaba Miklos Kindler, Giorgia Milli, Christel Ottosson, Kristian Euren, Lena Kajland Wilen, Maziar Nikberg
Detection of lymph node metastasis in colorectal cancer with the help of deep neural network
Presentation at ECP 2020, December.
Filippo Fraggetta
Clinical‑grade Computational Pathology: Alea Iacta Est
J Pathol Inform 2019, 10:38 (11 December 2019)
Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu, Daniel Hägg, Mats Andersson, Lars Björk Kristian Eurén, Cristina Svensson, Lena Kajland Wilén, Martin Hedlund
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
International Conference on Medical Imaging with Deep Learning (MIDL2019)
Nikolay Burlutskiy, Feng Gu, Lena Kajland Wilen, Max Backman, Patrick Micke
A Deep Learning Framework for Automatic Diagnosis in Lung Cancer
International Conference on Medical Imaging with Deep Learning (MIDL2018 in Amsterdam).
Lars Björk, Jonas Gustafsson, Feria Hikmet Noraddin, Kristian Eurén, Cecilia Lindskog
A new high-throughput auto-annotation method to detect and outline cancer areas in prostate biopsies
Presentation at ECDP 2018 Helsinki, Finland.
Peter Bandi, Oscar Geesink, Ludwig Jacobsson, Martin Hedlund et al.
From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge
IEEE Transaction on Medical Imaging PP(99):1-1, To be released.
Feng Gu, Nikolay Burlutskiy, Mats Andersson, and Lena Kajland Wilén.
Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images
MICCAI 2018 – COMPAY Workshop on computational pathology, Granada, Spain.
Mikael Rousson, Martin Hedlund, Mats Andersson, Ludwig Jacobsson, Gunnar Lathen, Bjorn Norell, Oscar Jimenez-del-Toro, Henning Mueller, Manfredo Atzori.
Tumor proliferation grading from whole slide images
SPIE Medical Imaging, 2018, Houston, Texas, United States.
Sebastian Otalora, Manfredo Atzori, Vincent Andrearczyk, and Henning Muller.
Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content
MICCAI 2018 – COMPAY Workshop on computational pathology, Granada, Spain.
Sebastian Otálora, et. al.
Determining the scale of image patches using a Deep Learning Approach
ISBI 2018. Washington D.C., USA, 2018.
Otálora s., Andrearczyk V., Atzori M., Müller H.
BIWGAN: Learning stable adversarial representations for prostate histopathology images
Medical Imaging Summer School 2018: Medical Imaging meets Deep Learning. Favignana, Italy.
Oscar Jimenez del Toro, Manfredo Atzori, Sebastian Otálora, Mats Andersson, Kristian Eurén, Martin Hedlund, Peter Rönnquist and Henning Müller.
Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score
SPIE Medical Imaging, pages 101400O-101400O-9, 2017.
Oscar Jimenez del Toro, Sebastian Otálora, Mats Andersson, Kristian Eurén, Martin Hedlund, Mikael Rousson, Henning Müller and Manfredo Atzori.
Elsevier book on Texture Analysis, chapter Analysis of Histopathology Images
From Traditional Machine Learning to Deep Learning, 2017.
Oscar Jimenez del Toro, Sebastian Otálora, Manfredo Atzori and Henning Müller.
Deep Multimodal Case-Based Retrieval for Large Histopathology Dataset
MICCAI 2017 workshop on Patch-based image analysis, Quebec City, Canada, 2017.
(The paper will be published in Springer LNCS)