Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
Benchmark on automatic six-month-old infant brain segmentation algorithms: the iSeg-2017 challenge
Accurate segmentation of infant brain magnetic resonance (MR) images into white matter
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
HyperDense-Net: a hyper-densely connected CNN for multi-modal image segmentation
Recently, dense connections have attracted substantial attention in computer vision
because they facilitate gradient flow and implicit deep supervision during training …
because they facilitate gradient flow and implicit deep supervision during training …
Inverted bell-curve-based ensemble of deep learning models for detection of COVID-19 from chest X-rays
Novel Coronavirus 2019 disease or COVID-19 is a viral disease caused by severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of chest X-rays (CXRs) has …
respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of chest X-rays (CXRs) has …
AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation
Whole brain segmentation of fine-grained structures using deep learning (DL) is a very
challenging task since the number of anatomical labels is very high compared to the number …
challenging task since the number of anatomical labels is very high compared to the number …
IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet
Accurate localization and segmentation of intervertebral disc (IVD) is crucial for the
assessment of spine disease diagnosis. Despite the technological advances in medical …
assessment of spine disease diagnosis. Despite the technological advances in medical …
Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities
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A multilevel features selection framework for skin lesion classification
Melanoma is considered to be one of the deadliest skin cancer types, whose occurring
frequency elevated in the last few years; its earlier diagnosis, however, significantly …
frequency elevated in the last few years; its earlier diagnosis, however, significantly …
Effectiveness of federated learning and CNN ensemble architectures for identifying brain tumors using MRI images
Medical institutions often revoke data access due to the privacy concern of patients.
Federated Learning (FL) is a collaborative learning paradigm that can generate an unbiased …
Federated Learning (FL) is a collaborative learning paradigm that can generate an unbiased …
Diminishing uncertainty within the training pool: Active learning for medical image segmentation
Active learning is a unique abstraction of machine learning techniques where the
model/algorithm could guide users for annotation of a set of data points that would be …
model/algorithm could guide users for annotation of a set of data points that would be …