High Performance Neural Network Inference, Streaming, and Visualization of Medical Images Using FAST. - Erik Smistad; Andreas Østvik; André Pedersen (IEEE Access, 2019)

Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture. - David Bouget; André Pedersen; Sayied Abdol Mohieb Hosainey; Johanna Vanel; Ole Solheim; Ingerid Reinertsen (CoRR, 2020)

Preliminary Processing and Analysis of an Adverse Event Dataset for Detecting Sepsis-Related Events. - Melissa Y. Yan; Lise Husby Høvik; André Pedersen; Lise Tuset Gustad; Øystein Nytrø (BIBM, 2021)

FastPathology: An Open-Source Platform for Deep Learning-Based Research and Decision Support in Digital Pathology. - André Pedersen; Marit Valla; Anna M. Bofin; Javier Pérez de Frutos; Ingerid Reinertsen; Erik Smistad (IEEE Access, 2021)

Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms. - David Bouget; André Pedersen; Sayied Abdol Mohieb Hosainey; Ole Solheim; Ingerid Reinertsen (CoRR, 2021)

Code-free development and deployment of deep segmentation models for digital pathology. - Henrik Sahlin Pettersen; Ilya Belevich; Elin Synnøve Røyset; Erik Smistad; Eija Jokitalo; Ingerid Reinertsen; Ingunn Bakke; André Pedersen (CoRR, 2021)

Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images. - André Pedersen; Erik Smistad; Tor V. Rise; Vibeke G. Dale; Henrik Sahlin Pettersen; Tor-Arne S. Nordmo; David Bouget; Ingerid Reinertsen; Marit Valla (CoRR, 2021)

Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation. - Vemund Fredriksen; Svein Ole M. Svele; André Pedersen; Thomas Langø; Gabriel Kiss; Frank Lindseth (CoRR, 2021)

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting. - David Bouget; André Pedersen; Asgeir S. Jakola; Vasileios Kavouridis; Kyrre Eeg Emblem; Roelant S. Eijgelaar; Ivar Kommers; Hilko Ardon; Frederik Barkhof; Lorenzo Bello; Mitchel S. Berger; Marco Conti Nibali; et al. (CoRR, 2022)

Train smarter, not harder: learning deep abdominal CT registration on scarce data. - Javier Pérez de Frutos; André Pedersen; Egidijus Pelanis; David Bouget; Shanmugapriya Survarachakan; Thomas Langø; Ole Jakob Elle; Frank Lindseth (CoRR, 2022)

The AGU-Net Architecture for Brain Tumor Segmentation: BraTS Challenges 2023. - David Bouget; André Pedersen; Ole Solheim; Ingerid Reinertsen (BraTS/CrossMoDA@MICCAI, 2023)

Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks. - Ragnhild Holden Helland; Alexandros Ferles; André Pedersen; Ivar Kommers; Hilko Ardon; Frederik Barkhof; Lorenzo Bello; Mitchel S. Berger; Tora Dunås; Marco Conti Nibali; Julia Furtner; Shawn Hervey-Jumper; et al. (CoRR, 2023)

Raidionics: an open software for pre- and postoperative central nervous system tumor segmentation and standardized reporting. - David Bouget; Demah Alsinan; Valeria Gaitan; Ragnhild Holden Helland; André Pedersen; Ole Solheim; Ingerid Reinertsen (CoRR, 2023)

AeroPath: An airway segmentation benchmark dataset with challenging pathology. - Karen-Helene Støverud; David Bouget; André Pedersen; Håkon Olav Leira; Thomas Langø; Erlend Fagertun Hofstad (CoRR, 2023)

Immunohistochemistry guided segmentation of benign epithelial cells, in situ lesions, and invasive epithelial cells in breast cancer slides. - Maren Høibø; André Pedersen; Vibeke Grotnes Dale; Sissel Marie Berget; Borgny Ytterhus; Cecilia Lindskog; Elisabeth Wik; Lars A. Akslen; Ingerid Reinertsen; Erik Smistad; Marit Valla (CoRR, 2023)

Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding. - David Bouget; André Pedersen; Johanna Vanel; Håkon Olav Leira; Thomas Langø (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2023)

Segmentation of Non-Small Cell Lung Carcinomas: Introducing DRU-Net and Multi-Lens Distortion. - Soroush Oskouei; Marit Valla; André Pedersen; Erik Smistad; Vibeke Grotnes Dale; Maren Høibø; Sissel Gyrid Freim Wahl; Mats Dehli Haugum; Thomas Langø; Maria Paula Ramnefjell; Lars Andreas Akslen; Gabriel Kiss; et al. (CoRR, 2024)