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CLANet: A comprehensive framework for cross-batch cell line identification using brightfield images
CLANet: A comprehensive framework for cross-batch cell line identification using brightfield images
Cell line authentication plays a crucial role in the biomedical field, ensuring researchers work with accurately identifie...
TransVFS: A spatio-temporal local–global transformer for vision-based force sensing during ultrasound-guided prostate biopsy
TransVFS: A spatio-temporal local–global transformer for vision-based force sensing during ultrasound-guided prostate biopsy
Prostate cancer (PCa) is the most prevalent malignant tumor in the male reproductive system and one of the main causes of ...
Tracking and mapping in medical computer vision: A review
Tracking and mapping in medical computer vision: A review
As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. T...
Mitosis detection, fast and slow: Robust and efficient detection of mitotic figures
Mitosis detection, fast and slow: Robust and efficient detection of mitotic figures
Counting of mitotic figures is a fundamental step in grading and prognostication of several cancers. However, manual mitos...
Digital twinning of the human ventricular activation sequence to Clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials
Digital twinning of the human ventricular activation sequence to Clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials
Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using human-based modelling an...
On the pitfalls of Batch Normalization for end-to-end video learning: A study on surgical workflow analysis
On the pitfalls of Batch Normalization for end-to-end video learning: A study on surgical workflow analysis
Batch Normalization (BatchNorm/BN) (Ioffe and Szegedy, 2015) is a highly effective regularizer in visual recognition tasks...
RNFLT2Vec: Artifact-corrected representation learning for retinal nerve fiber layer thickness maps
RNFLT2Vec: Artifact-corrected representation learning for retinal nerve fiber layer thickness maps
Glaucoma, the leading cause of irreversible blindness globally, is a progressive optic neuropathy characterized by irrever...
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
The brain's white matter connections (fiber tracts) and their tissue microstructure can be quantitatively mapped using dif...
Inferring brain causal and temporal-lag networks for recognizing abnormal patterns of dementia
Inferring brain causal and temporal-lag networks for recognizing abnormal patterns of dementia
Alzheimer’s disease (AD), accounting for approximately 60%–80% of dementia cases, is one of the most frequent forms of dem...
Transformer based multi-modal MRI fusion for prediction of post-menstrual age and neonatal brain development analysis
Transformer based multi-modal MRI fusion for prediction of post-menstrual age and neonatal brain development analysis
The early stages of human life, particularly the infant period (before 1 year old), are characterized by rapid changes in ...
Hybrid representation learning for cognitive diagnosis in late-life depression over 5 years with structural MRI
Hybrid representation learning for cognitive diagnosis in late-life depression over 5 years with structural MRI
Late-life depression (LLD), mild cognitive impairment (MCI), and dementia are prevalent disorders worldwide that affect ol...
Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning
Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning
Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as...
Privacy preserving image registration
Privacy preserving image registration
Image Registration is a crucial task in medical imaging applications, allowing to spatially align imaging features between...
Long-short diffeomorphism memory network for weakly-supervised ultrasound landmark tracking
Long-short diffeomorphism memory network for weakly-supervised ultrasound landmark tracking
Ultrasound is a promising medical imaging modality benefiting from low-cost and real-time acquisition. Accurate tracking o...
Task sub-type states decoding via group deep bidirectional recurrent neural network
Task sub-type states decoding via group deep bidirectional recurrent neural network
Decoding brain cognitive states from functional brain imaging data has attracted increasing attention in recent years (Coh...
Use of superpixels for improvement of inter-rater and intra-rater reliability during annotation of medical images
Use of superpixels for improvement of inter-rater and intra-rater reliability during annotation of medical images
Volume 94, May 2024, 103141Author links open overlay panel, , , , , , , Highlights•Superpixel presegmentation is proposed ...
STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution
STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution
Cardiac magnetic resonance imaging (MRI) is considered the gold standard for both visual and quantitative evaluation of he...
Anomaly-guided weakly supervised lesion segmentation on retinal OCT images
Anomaly-guided weakly supervised lesion segmentation on retinal OCT images
The management of a variety of vision-threatening retinal conditions can be substantially improved with the aid of imaging...
Constructing hierarchical attentive functional brain networks for early AD diagnosis
Constructing hierarchical attentive functional brain networks for early AD diagnosis
Alzheimer’s disease (AD), the most common form of dementia in elderly people, is an irreversible and incurable neurodegene...
CellViT: Vision Transformers for precise cell segmentation and classification
CellViT: Vision Transformers for precise cell segmentation and classification
Selma Ugurel studied medicine at the Heinrich-Heine University Düsseldorf and RWTH Aachen University (Germany). Subsequent...
Modeling annotator preference and stochastic annotation error for medical image segmentation
Modeling annotator preference and stochastic annotation error for medical image segmentation
Medical image segmentation plays a crucial role in delivering effective patient care in diagnostic and treatment practices...
Beam-wise dose composition learning for head and neck cancer dose prediction in radiotherapy
Beam-wise dose composition learning for head and neck cancer dose prediction in radiotherapy
Head and neck (H&N) cancer is a broad category of diverse cancer types, originating from various soft tissue, glands, ...
Multi-source multi-modal markers for Bayesian Networks: Application to the extremely preterm born brain
Multi-source multi-modal markers for Bayesian Networks: Application to the extremely preterm born brain
The preterm phenotype results from the interplay of multiple disorders affecting the brain and cognitive outcomes. Accurat...
Deep learning based synthesis of MRI, CT and PET: Review and analysis
Deep learning based synthesis of MRI, CT and PET: Review and analysis
Medical image synthesis represents a critical area of research in clinical decision-making, aiming to overcome the challen...
Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
Multi-sequence MRIs show different characteristics of protons within tissues, resulting in various image appearances of wa...
FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images
FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images
Intracellular protozoan parasites are responsible for dramatic infectious diseases such as malaria, leishmaniasis, Chagas ...
Riemannian frameworks for the harmonization of resting-state functional MRI scans
Riemannian frameworks for the harmonization of resting-state functional MRI scans
Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols c...
Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery
Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery
Established surgical navigation systems for pedicle screw placement have been proven to be accurate, but still reveal limi...
CartiMorph: A framework for automated knee articular cartilage morphometrics
CartiMorph: A framework for automated knee articular cartilage morphometrics
Knee articular cartilage morphometrics is an effective tool to derive imaging biomarkers for knee osteoarthritis (OA) (Gra...
A knowledge-interpretable multi-task learning framework for automated thyroid nodule diagnosis in ultrasound videos
A knowledge-interpretable multi-task learning framework for automated thyroid nodule diagnosis in ultrasound videos
Thyroid nodules, one of the most common diseases in the thyroid gland, pose a significant public health risk. Medical imag...
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