A5017246903- Image and Signal Denoising Methods
- Medical Image Segmentation Techniques
- Advanced Image Processing Techniques
- AI in cancer detection
- Advanced Image Fusion Techniques
- Image Retrieval and Classification Techniques
- Sparse and Compressive Sensing Techniques
- Colorectal Cancer Screening and Detection
- Brain Tumor Detection and Classification
- Gastrointestinal Bleeding Diagnosis and Treatment
- Advanced Vision and Imaging
- Cell Image Analysis Techniques
- Medical Imaging Techniques and Applications
- Single-cell and spatial transcriptomics
- Image Enhancement Techniques
- Radiomics and Machine Learning in Medical Imaging
- Digital Imaging for Blood Diseases
- Advanced Data Compression Techniques
- Inflammatory Bowel Disease
- Cutaneous Melanoma Detection and Management
- Generative Adversarial Networks and Image Synthesis
- Sentiment Analysis and Opinion Mining
- Video Surveillance and Tracking Methods
- Image Processing Techniques and Applications
- Numerical methods in inverse problems
University of Cincinnati
2017-2025
Cincinnati Children's Hospital Medical Center
2017-2025
University of Cincinnati Medical Center
2019-2024
SRM Institute of Science and Technology
2024
SASTRA University
2020
University of Missouri
2012-2019
Kitware (United States)
2019
Indian Institute of Technology Madras
2008-2019
University of California, Los Angeles
2019
University of Coimbra
2011-2019
Cytolytic T-cells play an essential role in the adaptive immune system by seeking out, binding and killing cells that present foreign antigens on their surface. An improved understanding of T-cell immunity will greatly aid development new cancer immunotherapies vaccines for life-threatening pathogens. Central to design such targeted therapies are computational methods predict non-native peptides elicit a response, however, we currently lack accurate immunogenicity inference methods. Another...
This paper focuses on the application of deep learning (DL) based model in analysis novel coronavirus disease (COVID-19) from X-ray images. The novelty this work is development a new DL algorithm termed as optimized residual network (CO-ResNet) for COVID-19. proposed CO-ResNet developed by applying hyperparameter tuning to conventional ResNet 101. applied dataset 5,935 images retrieved two publicly available datasets. By utilizing resizing, augmentation and normalization testing different...
Federated learning (FL) refers to a system in which central aggregator coordinates the efforts of several clients solve issues machine learning. This setting allows training data be dispersed order protect privacy each device. paper provides an overview federated systems, with focus on healthcare. FL is reviewed terms its frameworks, architectures and applications. It shown here that solves preceding shared global deep (DL) model via server. Inspired by rapid growth research, this examines...
Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of regulatory networks cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site ( TFBS ) Prediction Challenge highlighted value accessibility data prediction, establishing state-of-the-art methods for prediction from DNase-seq. However, more recent...
Edge preserving regularization using partial differential equation (PDE)-based methods although extensively studied and widely used for image restoration, still have limitations in adapting to local structures. We propose a spatially adaptive multiscale variable exponent-based anisotropic variational PDE method that overcomes current shortcomings, such as over smoothing staircasing artifacts, while retaining enhancing edge structures across scale. Our innovative model automatically balances...
In medical image processing, the skin lesion segmentation problem plays a vital role, because it is necessary to improve quality of extracting features classify lesion. Hence, imaging diagnosis systems can detect cancer early. It treat cancer, especially, melanoma - one most dangerous form cancer. this paper, we proposed two adaptive methods estimate global threshold used for based on normalization color models: RGB and XYZ. The our gives better result than Otsu method regarding grayscale...
Genetic algorithm (GA) is one of the well-known techniques from area evolutionary computation that plays a significant role in obtaining meaningful solutions to complex problems with large search space. GAs involve three fundamental operations after creating an initial population, namely selection, crossover, and mutation. The first task create appropriate population. Traditionally randomly selected population widely used as it simple efficient; however, generated may contain poor fitness....
We propose Adaptive Switching Weight Mean Filter (ASWMF) to remove the salt and pepper noise. Instead of using median or mean, ASWMF assigns value a switching weight mean (SWM) grey centre pixel an adaptive window. SWM is evaluated by eliminating all noisy pixels from window putting low for on diagonals high outside diagonals. can noise with various levels effectively. It not only successes low-density denoising, but also removes medium-density high-density impressively. In experiments, we...