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D-LEMA: Deep Learning Ensembles from Multiple Annotations – Application to Skin Lesion Segmentation
Medical image segmentation annotations suffer from inter/intra-observer ...
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Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation
The segmentation of skin lesions is a crucial task in clinical decision ...
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Patch-based Non-Local Bayesian Networks for Blind Confocal Microscopy Denoising
Confocal microscopy is essential for histopathologic cell visualization ...
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Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images
The semantic segmentation of skin lesions is an important and common ini...
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Deep Learning for Biomedical Image Reconstruction: A Survey
Medical imaging is an invaluable resource in medicine as it enables to p...
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Applying Artificial Intelligence to Glioma Imaging: Advances and Challenges
Primary brain tumors including gliomas continue to pose significant mana...
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Signed Input Regularization
Over-parameterized deep models usually over-fit to a given training dist...
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Deep Learning Models for Digital Pathology
Histopathology images; microscopy images of stained tissue biopsies cont...
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Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI
This paper presents a simple and effective generalization method for mag...
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Deep Semantic Segmentation of Natural and Medical Images: A Review
The (medical) image semantic segmentation task consists of classifying e...
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WhiteNNer-Blind Image Denoising via Noise Whiteness Priors
The accuracy of medical imaging-based diagnostics is directly impacted b...
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Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy
Recent developments in image acquisition literature have miniaturized th...
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Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis
Skin lesion segmentation is a vital task in skin cancer diagnosis and fu...
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Learning to Segment Skin Lesions from Noisy Annotations
Deep convolutional neural networks have driven substantial advancements ...
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Visual Diagnosis of Dermatological Disorders: Human and Machine Performance
Skin conditions are a global health concern, ranking the fourth highest ...
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Missing MRI Pulse Sequence Synthesis using Multi-Modal Generative Adversarial Network
Magnetic resonance imaging (MRI) is being increasingly utilized to asses...
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Improved Inference via Deep Input Transfer
Although numerous improvements have been made in the field of image segm...
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InfoMask: Masked Variational Latent Representation to Localize Chest Disease
The scarcity of richly annotated medical images is limiting supervised d...
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A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
The linear and non-flexible nature of deep convolutional models makes th...
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Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks
Recently, there have been several successful deep learning approaches fo...
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Star Shape Prior in Fully Convolutional Networks for Skin Lesion Segmentation
Semantic segmentation is an important preliminary step towards automatic...
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Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?
Confocal laser endomicroscopy (CLE) is a novel imaging modality that pro...
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Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation
Simultaneous segmentation of multiple organs from different medical imag...
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Select, Attend, and Transfer: Light, Learnable Skip Connections
Skip connections in deep networks have improved both segmentation and cl...
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Fully Convolutional Networks to Detect Clinical Dermoscopic Features
We use a pretrained fully convolutional neural network to detect clinica...
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Adaptable Precomputation for Random Walker Image Segmentation and Registration
The random walker (RW) algorithm is used for both image segmentation and...
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Incorporating prior knowledge in medical image segmentation: a survey
Medical image segmentation, the task of partitioning an image into meani...
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Multi-Label MRF Optimization via Least Squares s-t Cuts
There are many applications of graph cuts in computer vision, e.g. segme...
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Automatic Spatially-Adaptive Balancing of Energy Terms for Image Segmentation
Image segmentation techniques are predominately based on parameter-laden...
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