44 citations · 217 across the 15 of their papers we have counts for
17 papers
BabyFlow: 3D modeling of realistic and expressive infant faces
Antonia Alomar, Mireia Masias, Marius George Linguraru +2
Early detection of developmental disorders can be aided by analyzing infant craniofacial morphology, but modeling infant faces is challenging due to limited data and frequent spont…
A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network
Ariana M. Familiar, Anahita Fathi Kazerooni, Hannah Anderson +37
Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI
Abhijeet Parida, Zhifan Jiang, Syed Muhammad Anwar +6
For machine learning-based prognosis and diagnosis of rare diseases, such as pediatric brain tumors, it is necessary to gather medical imaging data from multiple clinical sites tha…
SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
Sunder Ali Khowaja, Kapal Dev, Syed Muhammad Anwar +1
Self-supervised learning in the federated learning paradigm has been gaining a lot of interest both in industry and research due to the collaborative learning capability on unlabel…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Maruf Adewole, Jeffrey D. Rudie, Anu Gbadamosi +48
Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 ye…
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +70
Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)
Hongwei Bran Li, Gian Marco Conte, Qingqiao Hu +62
Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input m…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
SPCXR: Self-supervised Pretraining using Chest X-rays Towards a Domain Specific Foundation Model
Syed Muhammad Anwar, Abhijeet Parida, Sara Atito +4
Chest X-rays (CXRs) are a widely used imaging modality for the diagnosis and prognosis of lung disease. The image analysis tasks vary. Examples include pathology detection and lung…
BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs
Araceli Morales, Antonio R. Porras, Marius George Linguraru +2
We present a 3D face reconstruction system that aims at recovering the 3D facial geometry of babies from uncalibrated photographs, BabyNet. Since the 3D facial geometry of babies d…
Communal Domain Learning for Registration in Drifted Image Spaces
Awais Mansoor, Marius George Linguraru
Designing a registration framework for images that do not share the same probability distribution is a major challenge in modern image analytics yet trivial task for the human visu…
Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection
Awais Mansoor, Antonio R. Porras, Marius George Linguraru
State-of-the-art methods for object detection use region proposal networks (RPN) to hypothesize object location. These networks simultaneously predicts object bounding boxes and \e…
Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review
Juan J. Cerrolaza, Mirella Lopez-Picazo, Ludovic Humbert +4
The medical image analysis field has traditionally been focused on the development of organ-, and disease-specific methods. Recently, the interest in the development of more 20 com…
A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning
Awais Mansoor, Juan J. Cerrolaza, Geovanny Perez +4
Computer-aided diagnosis (CAD) techniques for lung field segmentation from chest radiographs (CXR) have been proposed for adult cohorts, but rarely for pediatric subjects. Statisti…
Partitioned Shape Modeling with On-the-Fly Sparse Appearance Learning for Anterior Visual Pathway Segmentation
Awais Mansoor, Juan J. Cerrolaza, Robert A. Avery +1
MRI quantification of cranial nerves such as anterior visual pathway (AVP) in MRI is challenging due to their thin small size, structural variation along its path, and adjacent ana…