A5033066585- Planetary Science and Exploration
- Astro and Planetary Science
- Space Science and Extraterrestrial Life
- Space Exploration and Technology
- Geology and Paleoclimatology Research
- Brain Tumor Detection and Classification
- Advanced Neural Network Applications
- Medical Imaging and Analysis
- Acute Ischemic Stroke Management
- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Statistical Distribution Estimation and Applications
- Atrial Fibrillation Management and Outcomes
- Industrial Vision Systems and Defect Detection
- Scientific Research and Discoveries
- Advanced Radiotherapy Techniques
- Medical Imaging Techniques and Applications
- Spaceflight effects on biology
- Aeolian processes and effects
- Geochemistry and Geologic Mapping
- Financial Risk and Volatility Modeling
- Statistical Methods and Inference
- Methane Hydrates and Related Phenomena
- Atmospheric and Environmental Gas Dynamics
- ECG Monitoring and Analysis
The Open University
2017-2024
Clatterbridge Cancer Centre NHS Foundation Trust
2024
Chapman University
2020-2022
Atlanta VA Medical Center
2020
Emory University
2020
Kessler Foundation
2019
Rutgers New Jersey Medical School
2019
Rutgers, The State University of New Jersey
2019
Lancaster University
2010
Abstract Arrhythmia constitutes a problem with the rate or rhythm of heartbeat, and an early diagnosis is essential for timely inception successful treatment. We have jointly optimized entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains accuracy performance level professional cardiologists. The new approach comprised three-step noise reduction stage, novel feature extraction method optimal model finely tuned hyperparameters. carried out exhaustive...
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans stroke survivors would be a useful aid in patient diagnosis and treatment planning. It also greatly facilitate the study brain-behavior relationships by eliminating laborious step having human expert manually segment lesion on each scan. We propose multi-modal multi-path convolutional neural network system for automating segmentation. Our has nine end-to-end UNets that take as input 2-dimensional (2D)...
In this investigation a deep learning terrain classification system, the "Novelty or Anomaly Hunter – HiRISE" (NOAH-H), was used to classify High Resolution Imaging Science Experiment (HiRISE) images of Oxia Planum and Mawrth Vallis. A set ontological classes developed that covered variety surface textures aeolian bedforms present at both sites. Labelled type-examples these were train Deep Neural Network (DNN) perform semantic segmentation in order identify further HiRISE images. This...
Abstract Aeolian features at Oxia Planum—the 2023 landing site for the ExoMars Rosalind Franklin Rover (ERFR)—are important Mars exploration because they record information about past and current wind regimes, sand transport vectors, lend insight to abrasion, deposition, of granular material. To characterize regime erosional history Planum we used a combination manual observational machine‐learning techniques analyze morphometrics, distribution, orientation 10,753 aeolian bedforms...
This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for ExoMars Rosalind Franklin rover mission. The represents our current understanding of bedrock units and their relationships prior to Franklin's exploration this location. details 15 organised into 6 groups 7 textural surficial units. were identified using visible near-infrared remote sensing datasets. objectives are (i) identify where most astrobiologically relevant rocks likely be found, (ii) show hypotheses...
Polygonal networks of patterned ground are a common feature in cold-climate environments. They can form through the thermal contraction ice-cemented sediment (i.e. formed from fractures), or freezing and thawing ice by patterns clasts, deformation). The characteristics these landforms provide information about environmental conditions. Analogous polygonal forms have been observed on Mars leading to inferences We identified clastic features located around Lyot crater, (50°N, 30°E). These...
The area surrounding Lomonosov crater on Mars has a high density of seemingly organised boulder patterns. These form sorted polygons and stripes within kilometre scale blockfields, patches strewn ground which are common across the Martian latitudes. Several hypotheses have been suggested to explain formation clastic patterned Mars. It proposed that these structures could formed through freeze-thaw sorting, or conversely by interaction boulders with underlying fracture polygons. In this...
Abstract Purpose To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D‐magnetic resonance (4D‐MR) image data than do signals based on normal anatomy, reducing levels stitching artifacts within sorted lung volumes. Methods (4D‐MRI) scans were collected for 10 cancer patients using 2D T2‐weighted single‐shot turbo spin echo sequence, obtaining 25 repeat frames per slice. For each slice, tumor‐motion was generated the first principal component...
We applied a deep learning terrain classification system, the 'Novelty or Anomaly Hunter – HiRISE' (NOAH-H), originally developed for ExoMars landing sites in Oxia Planum and Mawrth Vallis, to Mars 2020 Perseverance rover site Jezero crater. NOAH-H successfully classified four HiRISE images of even though landforms study area were slightly different from those training dataset. mosaicked rasters compared them with manually generated photogeological map, Ingenuity helicopter images. find that...
We propose a fully 3D multi-path convolutional network to predict stroke lesions from brain MRI images. Our model has independent encoders for different modalities containing residual blocks, weighted feature fusion modalities, and modules combine encoder decoder features. Compared existing CNNs like DeepMedic, U-Net, AnatomyNet, our networks achieves the highest statistically significant cross-validation accuracy of 60.5% on large ATLAS benchmark 220 patients. also test multi-modal images...
We present a map of Oxia Planum, Mars, the landing site for ExoMars Rover. This shows surface texture and aeolian bedform distribution, classified using deep learning (DL) system. A hierarchical classification scheme was developed, categorising textures observed at site. then used to train DL network, 'Novelty or Anomaly Hunter – HiRISE' (NOAH-H). The applied across wider area than could have been mapped manually. result showed strong agreement with human-mapped areas reserved validation....
A deep learning (DL) terrain classification system, the Novelty and Anomaly Hunter – HiRISE (NOAH-H) was used to produce a map of Mawrth Vallis, Mars. With it, we digitised extent distribution transverse aeolian ridges (TARs), common type martian bedform. We present maps site, classifying into descriptive classes interpretive groups. TAR density are calculated, network output is compared manually produced density, highlighting differences in approach results between these methods. Even when...
The classical Box-Pierce and Ljung-Box tests for auto-correlation of residuals possess severe deviations from nominal type I error rates. Previous studies have attempted to address this issue by either revising existing or designing new techniques. Adjusted achieves the best results with respect attaining rates closer values. This research paper proposes a further correction adjusted test that possesses near perfect approach is based on an inflation rejection region all sample sizes lags...
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans stroke survivors would be a useful aid in patient diagnosis and treatment planning. We propose multi-modal multi-path convolutional neural network system for automating lesion segmentation. Our has nine end-to-end UNets that take as input 2-dimensional (2D) slices examines all three planes with different normalizations. Outputs these total paths are concatenated into 3D volume is then passed to output final...
Alexander Barrett considers some of the open questions about martian environment, and how choice potential landing sites for ExoMars might help to answer them.