Fulham, M.
* 2013: New Energy Framework With Distribution Descriptors for Image Segmentation, A
* 2013: Robust Model for Segmenting Images With/Without Intensity Inhomogeneities
* 2019: Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT
* 2019: Step-wise integration of deep class-specific learning for dermoscopic image segmentation
* 2019: Unsupervised Two-Path Neural Network for Cell Event Detection and Classification Using Spatiotemporal Patterns
* 2020: Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer
* 2020: Multi-Label classification of multi-modality skin lesion via hyper-connected convolutional neural network
* 2020: Unsupervised Domain Adaptation to Classify Medical Images Using Zero-Bias Convolutional Auto-Encoders and Context-Based Feature Augmentation
* 2022: attention-enhanced cross-task network to analyse lung nodule attributes in CT images, An
* 2022: Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images
Includes: Fulham, M. Fulham, M.[Michael]
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Fulham, M.J.[Michael J.]
* 2010: 3D neurological image retrieval with localized pathology-centric CMRGlc patterns
* 2010: Fully automated liver segmentation for low- and high- contrast CT volumes based on probabilistic atlases
* 2010: Structure-Adaptive Feature Extraction and Representation for Multi-modality Lung Images Retrieval
* 2011: Lung tumor delineation in PET-CT images using a downhill region growing and a Gaussian mixture model
* 2013: Automated Segmentation of Prostate MR Images Using Prior Knowledge Enhanced Random Walker
* 2013: Visibility-driven PET-CT visualisation with region of interest (ROI) segmentation
* 2014: Lesion Detection and Characterization With Context Driven Approximation in Thoracic FDG PET-CT Images of NSCLC Studies
* 2015: Large Margin Local Estimate With Applications to Medical Image Classification
* 2015: Locally Constrained Random Walk Approach for Airway Segmentation of Low-Contrast Computed Tomography (CT) Image, A
* 2017: Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation
Includes: Fulham, M.J.[Michael J.] Fulham, M.J. Fulham, M.J.[Micheal J.]
10 for Fulham, M.J.