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Initial condition assessment for reaction-diffusion glioma growth models: A translational MRI/histology (in)validation study.

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Segmentation of glandular epithelium in colorectal tumours to automatically compartmentalise IHC biomarker quantification: A deep learning approach., , , , , and . Medical Image Anal., (2018)Description Contrasting in Incremental Concept Formation.. EWSL, volume 482 of Lecture Notes in Computer Science, page 220-233. Springer, (1991)Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination., , and . Multiple Classifier Systems, volume 1857 of Lecture Notes in Computer Science, page 200-209. Springer, (2000)KI-67 hot-spots detection on glioblastoma tissue sections., , , , , and . ISBI, page 149-152. IEEE, (2010)SNOW: Semi-Supervised, Noisy And/Or Weak Data For Deep Learning In Digital Pathology., , and . ISBI, page 1869-1872. IEEE, (2019)Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model?, , , , , , , and . CoRR, (2021)Phase contrast image segmentation by weak watershed transform assembly., , , , and . ISBI, page 724-727. IEEE, (2008)High-throughput analysis of tissue-based biomarkers in digital pathology., , , , , and . EMBC, page 7732-7735. IEEE, (2015)Assessing Local Descriptors for Feature-Based Registration of Whole-Slide Images., , , , and . SIPAIM, page 1-4. IEEE, (2023)Finding the best channel for tissue segmentation in whole-slide images., , , and . SIPAIM, page 1-4. IEEE, (2023)