Search Results - "Garbi, Rafeef"

Leveraging voxel-wise segmentation uncertainty to improve reliability in assessment of paediatric dysplasia of the hip by Kannan, Arunkumar, Hodgson, Antony, Mulpuri, Kishore, Garbi, Rafeef

“…Purpose Estimating uncertainty in predictions made by neural networks is critically important for increasing the trust medical experts have in automatic data…”
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Correction to: Leveraging voxel-wise segmentation uncertainty to improve reliability in assessment of paediatric dysplasia of the hip by Kannan, Arunkumar, Hodgson, Antony, Mulpuri, Kishore, Garbi, Rafeef

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Augmented reality visualisation for orthopaedic surgical guidance with pre- and intra-operative multimodal image data fusion by El-Hariri, Houssam, Pandey, Prashant, Hodgson, Antony J, Garbi, Rafeef

“…Augmented reality (AR) has proven to be a useful, exciting technology in several areas of healthcare. AR may especially enhance the operator's experience in…”
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Ultrasound Bone Segmentation: A Scoping Review of Techniques and Validation Practices by Pandey, Prashant U., Quader, Niamul, Guy, Pierre, Garbi, Rafeef, Hodgson, Antony J.

“…Ultrasound bone segmentation is an important yet challenging task for many clinical applications. Several works have emerged attempting to improve and automate…”
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GC 2 : Generalizable Continual Classification of Medical Images by Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

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GC2: Generalizable Continual Classification of Medical Images by Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Deep learning models have achieved remarkable success in medical image classification. These models are typically trained once on the available annotated…”
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Cascaded Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation by Hussain, Mohammad Arafat, Hamarneh, Ghassan, Garbi, Rafeef

“…Kidney volume is an essential biomarker for a number of kidney disease diagnoses, for example, chronic kidney disease. Existing total kidney volume estimation…”
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Learnable image histograms-based deep radiomics for renal cell carcinoma grading and staging by Hussain, Mohammad Arafat, Hamarneh, Ghassan, Garbi, Rafeef

“…[Display omitted] •Proposed ImHistNet is capable of learning subtle textural features from raw images.•ImHistNet stratifies tumor and background textures, so…”
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GC 2 : Generalizable Continual Classification of Medical Images by Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Deep learning models have achieved remarkable success in medical image classification. These models are typically trained once on the available annotated…”
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BoosterNet: Improving Domain Generalization of Deep Neural Nets using Culpability-Ranked Features by Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Deep learning (DL) models trained to minimize empirical risk on a single domain often fail to generalize when applied to other domains. Model failures due to…”
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Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT by Hussain, Mohammad Arafat, Mirikharaji, Zahra, Momeny, Mohammad, Marhamati, Mahmoud, Neshat, Ali Asghar, Garbi, Rafeef, Hamarneh, Ghassan

“…Supervised deep learning has become a standard approach to solving medical image segmentation tasks. However, serious difficulties in attaining pixel-level…”
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Automatically Delineating Key Anatomy in 3-D Ultrasound Volumes for Hip Dysplasia Screening by El-Hariri, Houssam, Hodgson, Antony J., Mulpuri, Kishore, Garbi, Rafeef

“…Developmental dysplasia of the hip (DDH) metrics based on 3-D ultrasound have proven more reliable than those based on 2-D images, but to date have been based…”
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3-D Ultrasound Imaging Reliability of Measuring Dysplasia Metrics in Infants by Quader, Niamul, Hodgson, Antony J., Mulpuri, Kishore, Cooper, Anthony, Garbi, Rafeef

“…Developmental dysplasia of the hip is a hip abnormality that ranges from mild acetabular dysplasia to irreducible femoral head dislocations. While 2-D B-mode…”
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Cascaded Localization Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation by Hussain, Mohammad Arafat, Hamarneh, Ghassan, Garbi, Rafeef

“…Kidney volume is an essential biomarker for a number of kidney disease diagnoses, for example, chronic kidney disease. Existing total kidney volume estimation…”
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Continual-Zoo: Leveraging Zoo Models for Continual Classification of Medical Images by Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…In medical imaging, leveraging continual learning (CL) is key for models to adapt to new classes and data distributions without forgetting prior knowledge…”
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Debiasify: Self-Distillation for Unsupervised Bias Mitigation by Bayasi, Nourhan, Fayyad, Jamil, Hamarneh, Ghassan, Garbi, Rafeef, Najjaran, Homayoun

“…Simplicity bias poses a significant challenge in neural networks, often leading models to favor simpler solutions and inadvertently learn decision rules…”
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BiasPruner: Debiased Continual Learning for Medical Image Classification by Bayasi, Nourhan, Fayyad, Jamil, Bissoto, Alceu, Hamarneh, Ghassan, Garbi, Rafeef

“…Continual Learning (CL) is crucial for enabling networks to dynamically adapt as they learn new tasks sequentially, accommodating new data and classes without…”
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AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets by Du, Siyi, Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Skin lesion segmentation (SLS) plays an important role in skin lesion analysis. Vision transformers (ViTs) are considered an auspicious solution for SLS, but…”
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MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets by Du, Siyi, Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Despite its clinical utility, medical image segmentation (MIS) remains a daunting task due to images' inherent complexity and variability. Vision transformers…”
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FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning by Du, Siyi, Hers, Ben, Bayasi, Nourhan, Hamarneh, Ghassan, Garbi, Rafeef

“…Deep learning models have achieved great success in automating skin lesion diagnosis. However, the ethnic disparity in these models' predictions, where lesions…”
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