A5075622613- Medical Image Segmentation Techniques
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Retinal Imaging and Analysis
- Medical Imaging Techniques and Applications
- Optical Coherence Tomography Applications
- Radiomics and Machine Learning in Medical Imaging
- Advanced Image Processing Techniques
- Fetal and Pediatric Neurological Disorders
- Image and Signal Denoising Methods
- Glaucoma and retinal disorders
- Generative Adversarial Networks and Image Synthesis
- Cell Image Analysis Techniques
- Brain Tumor Detection and Classification
- Medical Imaging and Analysis
- Image Processing Techniques and Applications
- Sparse and Compressive Sensing Techniques
- Multiple Sclerosis Research Studies
- Functional Brain Connectivity Studies
- Digital Imaging for Blood Diseases
- Retinal and Optic Conditions
- Automotive and Human Injury Biomechanics
- AI in cancer detection
- Traumatic Brain Injury and Neurovascular Disturbances
- Vestibular and auditory disorders
Johns Hopkins University
2015-2024
Google (United States)
2023
Johns Hopkins Hospital
2018
University of Baltimore
2014-2016
Bellingham Technical College
2015
Optical coherence tomography (OCT) has proven to be an essential imaging modality for ophthalmology and is proving very important in neurology. OCT enables high resolution of the retina, both at optic nerve head macula. Macular retinal layer thicknesses provide useful diagnostic information have been shown correlate well with measures disease severity several diseases. Since manual segmentation these layers time consuming prone bias, automatic methods are critical full utilization this...
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical common practices related to organization has not yet been performed. In this paper, we present comprehensive conducted up now. We demonstrate importance and show lack quality control consequences. First, reproducibility interpretation results often hampered as only fraction relevant information typically provided. Second, rank...
Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of complicates the choice one method above others. We therefore established MRBrainS online evaluation framework evaluating (semi)automatic algorithms that segment gray matter (GM), white (WM), and cerebrospinal fluid (CSF) on 3T scans elderly subjects (65–80 y). Participants apply their to provided data, after which results are evaluated ranked. Full manual segmentations GM, WM, CSF available all used...
Image synthesis learns a transformation from the intensity features of an input image to yield different tissue contrast output image. This process has been shown have application in many medical analysis tasks including imputation, registration, and segmentation. To carry out synthesis, intensities images are typically scaled-i.e., normalized-both training learn testing when applying transformation, but it is not presently known what type scaling optimal. In this paper, we consider seven...
Abstract The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image segmentation algorithms. It offers standardized of accuracy which has proven useful. However, it diminishing insight when the number objects unknown, such as in white matter lesion multiple sclerosis (MS) patients. We present refinement finer grained parsing SDI results situations where unknown. explore these ideas with two case studies showing what can be learned from our presented studies. Our...
The performance of image analysis algorithms applied to magnetic resonance images is strongly influenced by the pulse sequences used acquire images. Algorithms are typically optimized for a targeted tissue contrast obtained from particular implementation sequence on specific scanner. There many practical situations, including multi-institution trials, rapid emergency scans, and scientific use historical data, where not acquired according an optimal protocol or desired entirely missing. This...
Synthesizing a CT image from an available MR has recently emerged as key goal in radiotherapy treatment planning for cancer patients. CycleGANs have achieved promising results on unsupervised MR-to-CT synthesis; however, because they no direct constraints between input and synthetic images, cycleGANs do not guarantee structural consistency these two images. This means that anatomical geometry can be shifted the clearly highly undesirable outcome given application. In this paper, we propose...
In magnetic resonance (MR) imaging, a lack of standardization in acquisition often causes pulse sequence-based contrast variations MR images from site to site, which impedes consistent measurements automatic analyses. this paper, we propose an unsupervised image harmonization approach, CALAMITI (Contrast Anatomy Learning and Analysis for Intensity Translation Integration), aims alleviate multi-site imaging. Designed using information bottleneck theory, learns globally disentangled latent...
The cerebellum plays a central role in sensory input, voluntary motor action, and many neuropsychological functions is involved brain diseases neurological disorders. Cerebellar parcellation from magnetic resonance images provides way to study regional cerebellar atrophy also an anatomical map for functional imaging. In recent comparison, multi-atlas approach proved be superior other methods including some based on convolutional neural networks (CNNs) which have considerable speed advantage....
Magnetic resonance imaging (MRI) is widely used for analyzing human brain structure and function. MRI extremely versatile can produce different tissue contrasts as required by the study design. For reasons such patient comfort, cost, improving technology, certain a cohort analysis may not have been acquired during session. This missing pulse sequence hampers consistent neuroanatomy research. One possible solution to synthesize sequence. paper proposes data-driven approach image synthesis,...