Nothing Personal, Strictly Christmas (TV Movie 1995) - IMDb
Lokale kræfter skal løfte idrætten - Gå til historien | Nordjyske.dk
Association between thoracic and third lumbar CT-derived muscle mass and density in Caucasian patients without chronic disease: a proof-of-concept study | European Radiology Experimental | Full Text
Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings | SpringerLink
IJERPH | Free Full-Text | Computer-Assisted Annotation of Digital H&E/SOX10 Dual Stains Generates High-Performing Convolutional Neural Network for Calculating Tumor Burden in H&E-Stained Cutaneous Melanoma
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Lasse ØSTERGAARD | Professor (Associate) | MSc, PhD | Aalborg University, Aalborg | Department of Health Science and Technology | Research profile
Palle havde 170.000 nordjyder under sine vinger: - Du skal have store ører og et varmt hjerte | Nordjyske.dk
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Ambassadors - Invest In Aalborg
Lasse Riis Østergaard – Associate Professor – Aalborg Universitet | LinkedIn
Lasse ØSTERGAARD | Professor (Associate) | MSc, PhD | Aalborg University, Aalborg | Department of Health Science and Technology | Research profile
Comparison of manual and automatic MR‐CT registration for radiotherapy of prostate cancer - Korsager - 2016 - Journal of Applied Clinical Medical Physics - Wiley Online Library
UNF | Når demens kan måles i millimeter
Handest Murer & Entreprenør ApS | Fårup
Lasse Riis Østergaard – Associate Professor – Aalborg Universitet | LinkedIn
IJERPH | Free Full-Text | Computer-Assisted Annotation of Digital H&E/SOX10 Dual Stains Generates High-Performing Convolutional Neural Network for Calculating Tumor Burden in H&E-Stained Cutaneous Melanoma
Lasse Riis Østergaard – Associate Professor – Aalborg Universitet | LinkedIn
Lasse Riis Østergaard – Associate Professor – Aalborg Universitet | LinkedIn
Nyheder 2015
Lasse Riis Østergaard – Associate Professor – Aalborg Universitet | LinkedIn
Deep learning in medical imaging - Artificial Intelligence at UQ - University of Queensland
Automatic emphysema detection using weakly labeled HRCT lung images | PLOS ONE
