Results 61 to 70 of about 1,028 (168)

Histopathology Image Enhancement Using Multi‐Resolution Deep Learning Techniques

IET Image Processing, Volume 19, Issue 1, January/December 2025.
Accurate analysis of histopathology images is critical for reliable disease diagnosis and effective treatment planning. However, the resolution limitations of digital pathology scanners can hinder the visibility of fine cellular details, potentially impacting diagnostic accuracy and patient outcomes. In this study, we present a comprehensive comparison
Meriem Touhami, Zaka Ur Rehman, Md Jahid Hasan, Mohammad Faizal Ahmad Fauzi, Sarina Binti Mansor   +4 more
wiley   +1 more source

Denoising of CT and MRI Images Using Decomposition-Based Curvelet Thresholding and Classical Filtering Techniques

Applied Sciences
Medical image denoising is crucial for enhancing the diagnostic accuracy of CT and MRI images. This paper presents a modular hybrid framework that combines multiscale decomposition techniques (Empirical Mode Decomposition, Variational Mode Decomposition,
Mahmoud Nasr, Krzysztof Brzostowski, Rafał Obuchowicz, Adam Piórkowski   +3 more
doaj   +1 more source

FUSION OF WAVELET AND CURVELET COEFFICIENTS FOR GRAY TEXTURE CLASSIFICATION [PDF]

ICTACT Journal on Image and Video Processing, 2014
This study presents a framework for gray texture classification based on the fusion of wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT) and Discrete Curvelet Transform (DCT) are analyzed.
M. Santhanalakshmi, K. Nirmala
doaj  

Fake Fingerprint Classification Using Hybrid Features Learning With Gradient Boosting

Applied Computational Intelligence and Soft Computing, Volume 2025, Issue 1, 2025.
Biometric security systems must be able to detect phony fingerprints to provide reliable authentication. The findings of this study suggest a hybrid approach to the detection of fake fingerprints that uses information on the texture and shape of the fingerprint.
Muhammad Salman Ali, Arslan Akram, Javed Rashid, Muhammad Arfan Jaffar, Dilawar Shah, Shujaat Ali, Muhammad Tahir, Ridha Ejbali   +7 more
wiley   +1 more source

CURVELET-BASED FREQUENCY-AWARE FEATURE ENHANCEMENT FOR DEEPFAKE DETECTION

Science Journal of University of Zakho
The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising serious concerns about digital trust.
Salar Adel Sabri, Ramadhan J Mstafa
doaj   +1 more source

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

BMC Bioinformatics, 2011
Background Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA ...
Pham Tuan D, Zhang Bailing
doaj   +1 more source

Automatic Choroidal Segmentation in Optical Coherence Tomography Images Based on Curvelet Transform and Graph Theory. [PDF]

J Med Signals Sens, 2023
Eghtedar RA, Esmaeili M, Peyman A, Akhlaghi M, Rasta SH.   +4 more
europepmc   +1 more source

Curvelet Transform-Based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy. [PDF]

IEEE Trans Med Imaging, 2022
You Q, Trzasko JD, Lowerison MR, Chen X, Dong Z, ChandraSekaran NV, Llano DA, Chen S, Song P.   +8 more
europepmc   +1 more source

Leveling method for airborne electromagnetic data based on the curvelet transform and adaptive group-sparse variational model

Earth, Planets and Space
In airborne electromagnetic data processing, correcting leveling errors is critical for ensuring data accuracy. Traditional leveling methods predominantly rely on time-domain and frequency-domain analysis to characterize leveling errors.
Qiong Zhang, Xin Chen, Haomiao Wang, Zhonghang Ji, Fei Yan, Yunqing Liu   +5 more
doaj   +1 more source

3D curvelet transforms and astronomical data restoration

Applied and Computational Harmonic Analysis, 2010
The authors extend the curvelet transform from 2D to 3D. They propose two new decompositions, the BeamCurvelet and the RidCurvelet. The authors show that these new 3D transforms are useful for different applications such as filament detection, 3D cosmological data denoising and inpainting.
Woiselle, Arnaud, Starck, Jean-Luc, Fadili, Jalal M.   +2 more
openaire   +4 more sources