Deep learning for image enhancement and correction in magnetic resonance imaging—state-of-the-art and challenges
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical
diagnoses and research which underpin many recent breakthroughs in medicine and …
diagnoses and research which underpin many recent breakthroughs in medicine and …
Computer-based segmentation of cancerous tissues in biomedical images using enhanced deep learning model
S Tripathi, N Sharma - IETE Technical Review, 2022 - Taylor & Francis
In this manuscript, we proposed an automatic segmentation method which was developed
using the depth-wise separable convolution with bottleneck connections. The data were …
using the depth-wise separable convolution with bottleneck connections. The data were …
An augmented deep learning network with noise suppression feature for efficient segmentation of magnetic resonance images
The segmentation of cardiac MR images requires extensive attention as it needs a high level
of care and analysis for the diagnosis of affected part. The advent of deep learning …
of care and analysis for the diagnosis of affected part. The advent of deep learning …
Segmentation of brain tumour in MR images using modified deep learning network
This paper presents a modified segmentation network for brain tumour segmentation in
Magnetic Resonance Images. The early detection of brain tumour is quite mandatory for …
Magnetic Resonance Images. The early detection of brain tumour is quite mandatory for …
[HTML][HTML] Self-Supervised and Zero-Shot Learning in Multi-Modal Raman Light Sheet Microscopy
P Kumari, J Kern, M Raedle - Sensors, 2024 - mdpi.com
Advancements in Raman light sheet microscopy have provided a powerful, non-invasive,
marker-free method for imaging complex 3D biological structures, such as cell cultures and …
marker-free method for imaging complex 3D biological structures, such as cell cultures and …
Discriminative learning based dual channel denoising network for removal of noise from MR images
S Tripathi, DC Pandey - 2022 10th International Conference on …, 2022 - ieeexplore.ieee.org
The presented manuscript proposes a dual path denoising network for removal of Rician
noise from Magnetic Resonance Images (MRI). Noise is an undesired property which gets …
noise from Magnetic Resonance Images (MRI). Noise is an undesired property which gets …
DEEP ENSEMBLE METHODS FOR IDENTIFICATION OF MALICIOUS TISSUES IN NOISY BREAST HISTOPATHOLOGICAL IMAGES
S Tripathi, N Sharma - Biomedical Engineering: Applications, Basis …, 2024 - World Scientific
This work addresses the issues of noise and tissue appearance fluctuations in
histopathology image classification by using a novel deep ensemble method. The …
histopathology image classification by using a novel deep ensemble method. The …
Hearing loss classification via AlexNet and Support Vector Machine
J Wang - EAI Endorsed Transactions on AI and Robotics, 2023 - eudl.eu
This paper presents a new method for detecting hearing loss. Our approach is first to use
AlexNet to extract the features. Then, we use the Support Vector Machine as a classifier to …
AlexNet to extract the features. Then, we use the Support Vector Machine as a classifier to …
[HTML][HTML] 基于滤波方法和矩阵低秩稀疏分解的遥感图像去噪算法
吕慧， 李喆 - Optoelectronics, 2022 - hanspub.org
针对遥感图像在形成, 传输和处理过程中产生的椒盐噪声问题, 设计了一种结合中值滤波,
矩阵低秩分解与导向滤波的遥感图像去噪算法. 给定含噪图像, 该算法首先对图像进行有互相 …
矩阵低秩分解与导向滤波的遥感图像去噪算法. 给定含噪图像, 该算法首先对图像进行有互相 …
Automatic detection of Gibbs artefact in MR images with transfer learning approach
L Kocet, K Romarič, J Žibert - Technology and Health Care, 2023 - content.iospress.com
BACKGROUND: Quality control of magnetic resonance imaging includes image validation,
which covers also artefact detection. The daily manual review of magnetic resonance …
which covers also artefact detection. The daily manual review of magnetic resonance …