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NYU Dataset
Benchmark Dataset for Automatic Glottis Segmentation
- Alternate Title(s)
- BAGLS dataset
- Authors
- Pablo GomezAndreas M. KistPatrick SchlegelDavid A. Berry10 more author(s)...
- Description
The Benchmark for Automatic Glottis Segmentation (BAGLS) dataset contains 59,250 high-speed laryngeal videoendoscopy frames and individually annotated segmentation masks obtained from anonymized recordings of 640 consenting subjects across multiple hospitals in Europe and the United States. Participating institutions were Boston University; Louisiana State University; New York University; Sint-Augustinus...
- Subject
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Anatomy
- Access Rights
- Free to All
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NYU Dataset
Multi-Contrast MRI of the Mouse Brain Estimates Histological Staining Intensity
- Authors
- Zifei LiangChoong H. LeeTanzil M. ArefinZijun Dong6 more author(s)...
- Description
Magnetic resonance imaging (MRI) can image brain structure non-invasively and without ionizing radiation. However, inferring histopathological information from MRI remains challenging due to lack of direct links between MRI signals and cellular structures. This study showed that deep convolutional neural networks can estimate histological staining intensity directly from MRI signals developed using...
- Subject
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AnatomyNeuroscience
- Access Rights
- Free to All
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NYU Dataset
Radiologist and Deep Neural Network Predictions for Low-pass Filtered Mammograms
- Authors
- Taro MakinoStanisław JastrzębskiWitold OleszkiewiczCelin Chacko17 more author(s)...
- Description
Investigators manipulated images from the NYU Breast Cancer Screening Dataset to identify differences in the the features of perception used in diagnosis by radiologists versus deep neural networks (DNNs). Two studies were conducted. In the reader study, a set of 720 exams were processed with Gaussian low-pass filtering at varying severity levels and ten radiologists and five DNNs (trained on unperturbed...
- Subject
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Cancer
- Access Rights
- Free to All
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NYU Dataset
Automatic Mapping of Multiplexed Social Receptive Fields
- Authors
- Christian L. EbbesenRobert C. Froemke
- Description
Social interactions strongly impact the brain and the body. However, high-resolution descriptions of these important physical interactions and their neural correlates are lacking. This study described a hardware/software system and analysis pipeline that combines 3D videography, deep learning, physical modeling, and GPU-accelerated robust optimization with automatic analysis of neuronal receptive fields...
- Subject
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Neuroscience
- Access Rights
- Free to All
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NYU Dataset
In Utero Assessment of the Human Neural Connectome and Later Child Behavior
- Authors
- Moriah E. Thomason
- Description
To examine the association between fetal behavior and brain development through childhood, investigators conducted a longitudinal study with 120 normal fetuses in utero through 36 months of age recruited between 2011 and 2018 from Hutzel Women’s Hospital in Detroit, Michigan using continuous four‐dimensional functional magnetic resonance imaging (fMRI). Twelve‐minute fMRI scans were conducted in 120...
- Subject
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Mental HealthNeurosciencePregnancy
- Access Rights
- Free to AllApplication Required
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NYU Dataset
Mapping the Landscape of Histomorphological Cancer Phenotypes Using Self-Supervised Learning on Unannotated Pathology Slides
- Authors
- Adalberto Claudio QuirosNicolas CoudrayAnna H. YeatonXinyu Yang12 more author(s)...
- Description
Histomorphological Phenotype Learning (HPL) was developed as a self-supervised methodology to discriminatory features in microscopy images to aid in cancer diagnosis and management. The methodology partitions whole slide images (WSIs) into meaningful Histomorphological Phenotype Clusters (HPCs) that can be used to define and quantify morphological phenotypes which recur within and between cases. HPL...
- Subject
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CancerChronic Disease
- Access Rights
- Free to AllAuthor Approval Required
