Medical Image Learning with Limited and Noisy Data
Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings
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Marius George Linguraru
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Article
Open AccessCranial bone thickness and density anomalies quantified from CT images can identify chronic increased intracranial pressure
The diagnosis of chronic increased intracranial pressure (IIP)is often based on subjective evaluation or clinical metrics with low predictive value. We aimed to quantify cranial bone changes associated with pe...
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Article
Open AccessData-driven cranial suture growth model enables predicting phenotypes of craniosynostosis
We present the first data-driven pediatric model that explains cranial sutural growth in the pediatric population. We segmented the cranial bones in the neurocranium from the cross-sectional CT images of 2068 ...
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Book and Conference Proceedings
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Book and Conference Proceedings
Clinical Image-Based Procedures
11th Workshop, CLIP 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
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Chapter and Conference Paper
Brain Tumor Segmentation in Multi-parametric Magnetic Resonance Imaging Using Model Ensembling and Super-resolution
Brain tumor segmentation in MRI offers critical quantitative imaging data to characterize and improve prognosis. The International Brain Tumor Segmentation (BraTS) Challenge provides a unique opportunity to en...
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Chapter and Conference Paper
Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings
Rheumatic heart disease (RHD) is a common medical condition in children in which acute rheumatic fever causes permanent damage to the heart valves, thus impairing the heart’s ability to pump blood. Doppler ech...
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Chapter and Conference Paper
Learning with Context Encoding for Single-Stage Cranial Bone Labeling and Landmark Localization
Automatic anatomical segmentation and landmark localization in medical images are important tasks during craniofacial analysis. While deep neural networks have been recently applied to segment cranial bones an...
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Book and Conference Proceedings
Medical Image Learning with Limited and Noisy Data
First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
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Article
Federated learning for predicting clinical outcomes in patients with COVID-19
Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used ...
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Article
Three-dimensional photography for intraoperative morphometric analysis in metopic craniosynostosis surgery
Surgical correction of metopic craniosynostosis typically involves open cranial vault remodeling. Accurate translation of the virtual surgical plan into the operating room is challenging due to the lack of too...
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Chapter and Conference Paper
Standardized Analysis of Kidney Ultrasound Images for the Prediction of Pediatric Hydronephrosis Severity
Congenital hydronephrosis, which is the dilatation of the renal collecting system, is common in children, resolving in most and treatable in the remaining 25%. Sonography is routinely used for hydronephrosis d...
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Book and Conference Proceedings
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings
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Article
Open AccessNeurocranium thickness map** in early childhood
The neurocranium changes rapidly in early childhood to accommodate the growing brain. Developmental disorders and environmental factors such as sleep position may lead to abnormal neurocranial maturation. Ther...
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Book and Conference Proceedings
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings
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Chapter and Conference Paper
Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation
Deep learning strategies have become ubiquitous optimization tools for medical image analysis. With the appropriate amount of data, these approaches outperform classic methodologies in a variety of image proce...
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Article
Liver segmentation from low-radiation-dose pediatric computed tomography using patient-specific, statistical modeling
The pediatric computed tomography (CT) volume is acquired at a low dose because radiation is harmful to young children. Consequently, the pediatric CT volume has lower signal-to-noise ratio, which makes organ ...
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Article
Ventricular shape evaluation on early ultrasound predicts post-hemorrhagic hydrocephalus
To compare the ability of ventricular morphology on cranial ultrasound (CUS) versus standard clinical variables to predict the need for temporizing cerebrospinal fluid drainage in newborns with intraventricula...
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Book and Conference Proceedings
Adolescent Brain Cognitive Development Neurocognitive Prediction
First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings
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Book and Conference Proceedings
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures
First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
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Chapter and Conference Paper
Three-Dimensional Face Reconstruction from Uncalibrated Photographs: Application to Early Detection of Genetic Syndromes
Facial analysis from photography supports the early identification of genetic syndromes, but clinically-acquired uncalibrated images suffer from image pose and illumination variability. Although 3D photograph...
