4 citations · 17 across the 17 of their papers we have counts for
17 papers
Deep-and-Wide Learning: Enhancing Data-Driven Inference via Synergistic Learning of Inter- and Intra-Data Representations
Md Tauhidul Islam, Lei Xing
Advancements in deep learning are revolutionizing science and engineering. The immense success of deep learning is largely due to its ability to extract essential high-dimensional…
Discovering distinctive elements of biomedical datasets for high-performance exploration
Md Tauhidul Islam, Lei Xing
The human brain represents an object by small elements and distinguishes two objects based on the difference in elements. Discovering the distinctive elements of high-dimensional d…
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images
Chulong Zhang, Yuming Jiang, Na Li +9
Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-m…
Learning Image Representations for Content Based Image Retrieval of Radiotherapy Treatment Plans
Charles Huang, Varun Vasudevan, Oscar Pastor-Serrano +7
Objective: Knowledge based planning (KBP) typically involves training an end-to-end deep learning model to predict dose distributions. However, training end-to-end methods may be a…
Image Classification using Graph Neural Network and Multiscale Wavelet Superpixels
Varun Vasudevan, Maxime Bassenne, Md Tauhidul Islam +1
Prior studies using graph neural networks (GNNs) for image classification have focused on graphs generated from a regular grid of pixels or similar-sized superpixels. In the latter…
Self-supervised Feature Learning via Exploiting Multi-modal Data for Retinal Disease Diagnosis
Xiaomeng Li, Mengyu Jia, Md Tauhidul Islam +2
The automatic diagnosis of various retinal diseases from fundus images is important to support clinical decision-making. However, developing such automatic solutions is challenging…
A spline interpolation based data reconstruction technique for estimation of strain time constant in ultrasound poroelastography
Md Tauhidul Islam, Raffaella Righetti
Ultrasound poroelastography is a cost-effective non-invasive imaging technique, which is able to reconstruct several mechanical parameters of cancer and normal tissue such as Young…
Non-invasive assessment of the spatial and temporal distributions of interstitial fluid pressure, fluid velocity and fluid flow in cancers in vivo
Md Tauhidul Islam, Ennio Tasciotti, Raffaella Righetti
Interstitial fluid pressure (IFP), interstitial fluid velocity (IFV), interstitial permeability (IP) and vascular permeability (VP) are cancer mechanopathological parameters of gre…
Non-invasive imaging of Young's modulus and Poisson's ratio in cancers in vivo
Md Tauhidul Islam, Songyuan Tang, Chiara Liverani +2
Objective: Alterations of Young's modulus (YM) and Poisson's ratio (PR) in biological tissues are often early indicators of the onset of pathological conditions. Knowledge of these…
A novel filter for accurate estimation of fluid pressure and fluid velocity using poroelastography
Md Tauhidul Islam, Raffaella Righetti
Fluid pressure and fluid velocity carry important information for cancer diagnosis, prognosis and treatment. Recent work has demonstrated that estimation of these parameters is the…
Speech Enhancement Based on Non-stationary Noise-driven Geometric Spectral Subtraction and Phase Spectrum Compensation
Md Tauhidul Islam, Udoy Saha, K. T. Shahid +2
In this paper, a speech enhancement method based on noise compensation performed on short time magnitude as well phase spectra is presented. Unlike the conventional geometric appro…
Enhancement of Noisy Speech exploiting a Gaussian Modeling based Threshold and a PDF Dependent Thresholding Function
Md Tauhidul Islam, Celia Shahnaz
This paper presents a speech enhancement method, where an adaptive threshold is statistically determined based on Gaussian modeling of Teager energy (TE) operated perceptual wavele…
Speech Enhancement in Adverse Environments Based on Non-stationary Noise-driven Spectral Subtraction and SNR-dependent Phase Compensation
Md Tauhidul Islam, Asaduzzaman, Celia Shahnaz +2
A two-step enhancement method based on spectral subtraction and phase spectrum compensation is presented in this paper for noisy speeches in adverse environments involving non-stat…
Enhancement of Noisy Speech Exploiting an Exponential Model Based Threshold and a Custom Thresholding Function in Perceptual Wavelet Packet Domain
Md Tauhidul Islam, Celia Shahnaz, Wei-Ping Zhu +1
For enhancement of noisy speech, a method of threshold determination based on modeling of Teager energy (TE) operated perceptual wavelet packet (PWP) coefficients of the noisy spee…
Enhancement of Noisy Speech with Low Speech Distortion Based on Probabilistic Geometric Spectral Subtraction
Md Tauhidul Islam, Celia Shahnaz, Wei-Ping Zhu +1
A speech enhancement method based on probabilistic geometric approach to spectral subtraction (PGA) performed on short time magnitude spectrum is presented in this paper. A confide…
Modeling of Teager Energy Operated Perceptual Wavelet Packet Coefficients with an Erlang-2 PDF for Real Time Enhancement of Noisy Speech
Md Tauhidul Islam, Celia Shahnaz, Wei-Ping Zhu +1
In this paper, for real time enhancement of noisy speech, a method of threshold determination based on modeling of Teager energy (TE) operated perceptual wavelet packet (PWP) coeff…
A Divide and Conquer Strategy for Musical Noise-free Speech Enhancement in Adverse Environments
Md Tauhidul Islam, Celia Shahnaz, Wei-Ping Zhu +1
A divide and conquer strategy for enhancement of noisy speeches in adverse environments involving lower levels of SNR is presented in this paper, where the total system of speech e…