Article
Geochemistry & Geophysics
Gustavo de Camargo, Guilherme Holsbach Costa
Summary: Phase correlation image registration is a suitable approach to global motions. However, under real application conditions, it often leads to incorrect rotation estimations. This study reveals that the problem is caused by the mapping from Cartesian to Polar coordinates, which has been overlooked for the past 25 years. Preliminary results demonstrate the solution to this problem and the improvement in performance.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv
Summary: This paper introduces a novel deep learning framework called HueNet for differentiable construction of intensity and joint histograms. It demonstrates the applicability of HueNet to paired and unpaired image-to-image translation problems by augmenting a generative neural network with histogram layers. The paper also defines two new histogram-based loss functions for constraining the structural appearance and color distribution of the synthesized output image.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Debapriya Sengupta, Phalguni Gupta, Arindam Biswas
Summary: Image registration, the process of aligning one image in the coordinate system of another, plays a vital role in the medical field. Mutual information-based algorithms have significantly advanced medical image registration, and new developments, including deep neural network-based algorithms, continue to emerge. This paper provides a survey of these algorithms, discussing their development, major works, comparative studies, and the post-mutual information era in medical image registration.
Article
Computer Science, Information Systems
Sanjay Agrawal, Rutuparna Panda, P. K. Mishro, Ajith Abraham
Summary: A novel joint histogram equalization (JHE) based technique is proposed in this research to improve the contrast of an image by utilizing the information among each pixel and its neighbors. The experimental analysis shows that this method outperforms the state-of-the-art histogram equalization algorithms in contrast enhancement, even for images with a narrow dynamic range.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Kouta Hirotaki, Shunsuke Moriya, Tsunemichi Akita, Kazutoshi Yokoyama, Takeji Sakae
Summary: The study proposes a method to improve mutual-information-based automatic image registration by using a contrast enhancement filter (CEF). The results show that using CEF preprocessing can enhance the normalized mutual information (NMI) and registration accuracy, achieving similar accuracy to experienced therapists.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
(2022)
Article
Multidisciplinary Sciences
Muniba Ashfaq, Nasru Minallah, Jaroslav Frnda, Ladislav Behan
Summary: This study presents a new multi-modal image registration technique, called MFRGA, based on a genetic algorithm, which effectively handles high levels of noise and INU. Results show that MFRGA outperforms traditional genetic algorithms in registration errors and provides more accurate segmentation of brain structures.
Article
Optics
Pranav Wani, Gokul Krishnan, Timothy O'Connor, Bahram Javidi
Summary: This paper presents an information-theoretic approach for simulating and evaluating the integral imaging capture and reconstruction process. Mutual information is used as a metric for evaluating the fidelity of the reconstructed 3D scene. The paper also considers passive depth estimation using mutual information and evaluates the effect of partial occlusion in integral imaging 3D reconstruction.
Article
Computer Science, Artificial Intelligence
Henrik G. Jensen, Francois Lauze, Sune Darkner
Summary: The study introduces an information-theoretic approach for image registration, specifically for DWI images with directional information. By expanding the hierarchical scale-space model based on LOR-DWI density, the integration, spatial, directional, and intensity scales are effectively optimized. Additionally, nonrigid deformations are addressed to handle classic challenges in DWI registrations.
JOURNAL OF MATHEMATICAL IMAGING AND VISION
(2022)
Article
Engineering, Multidisciplinary
Nasra Begum, Noor Badshah, Lavdie Rada, Adela Ademaj, Muniba Ashfaq, Hadia Atta
Summary: Joint image segmentation and registration is crucial in image preprocessing, but it is challenging due to sensitivity to noise. This study proposes an improved joint model using the Bhattacharyya distance measure to enhance noise robustness compared to existing models. The proposed model achieves satisfactory results in medical and synthetic noisy images, outperforming the existing model based on the Bhattacharyya distance measure.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Engineering, Biomedical
Vinicius Pavanelli Vianna, Luiz Otavio Murta
Summary: The study introduces Generalized MI (GMI) using Tsallis entropy to improve affine registration, resulting in significantly prolonged registration ranges in the metric space.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Computer Science, Information Systems
Qingqing Li, Guangliang Han, Peixun Liu, Hang Yang, Jiajia Wu, Dongxu Liu
Summary: A novel fusion framework for infrared and visible image fusion is proposed in this paper, which utilizes a multi-level image decomposition method to obtain base and detail layers of the source image, and introduces innovative fusion strategies and efficient approaches for handling these layers. Experimental results demonstrate the superior performance of the proposed framework compared to fifteen classical and advanced fusion methods.
Article
Computer Science, Information Systems
Abdenour Hacine-Gharbi, Philippe Ravier
Summary: A mutual information-based feature selection method was proposed in this study, aiming to minimize MI estimation errors by considering different histogram binning choices. Various selection strategies were implemented and applied on 39-features vectors and large dimension vectors. Results showed that LMSE bin choice provided the best MI estimation and ensured a minimal number of features, while the CMI strategy achieved significant reduction.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Pengcheng Hao, Meng Yang, Nanning Zheng
Summary: In this paper, a novel method is proposed for subjective low-light image enhancement by incorporating foreground saliency detection and Retinex techniques, which effectively improve the visual perception of low-light images.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Biomedical
Sunita Samant, Pradipta Kumar Nanda, Ashish Ghosh, Adya Kinkar Panda
Summary: This paper proposes a new scheme for registering brain MR and CT images under noisy conditions. The scheme is based on the concept of mutual information and extends it to feature space-based registration. The 2D joint histogram of the noisy MR and CT images is computed and assumed to be a degraded version of the true joint histogram. The true joint histogram is modeled as a Markov Random Field and estimated from the degraded version using MAP estimation. The optimal registration parameter is determined by maximizing the mutual information, which is modeled as a multivariate Gaussian distribution. The scheme is tested with patient slices from the RIRE database and demonstrates improved performance compared to existing schemes, especially in high noisy conditions.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Engineering, Electrical & Electronic
Jiebang Wang, Gang Liu, Xiangbo Zhang, Haojie Tang
Summary: In this paper, a saliency-based method for infrared and visible light fusion is proposed. By segmenting the images into thermal targets and backgrounds and enhancing them based on semantic importance information, the visual effects of the fused image are improved.
SIGNAL IMAGE AND VIDEO PROCESSING
(2023)
Article
Computer Science, Software Engineering
Qiegen Liu, Sanqian Li, Jiaojiao Xiong, Binjie Qin
Article
Radiology, Nuclear Medicine & Medical Imaging
Jun-Feng Xiong, Tian-Ying Jia, Xiao-Yang Li, Wen Yu, Zhi-Yong Xu, Xu-Wei Cai, Ling Fu, Jie Zhang, Bin-Jie Qin, Xiao-Long Fu, Jun Zhao
BRITISH JOURNAL OF RADIOLOGY
(2018)
Article
Computer Science, Artificial Intelligence
Minghui Zhang, Yiling Liu, Guanyu Li, Binjie Qin, Qiegen Liu
PATTERN ANALYSIS AND APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Binjie Qin, Mingxin Jin, Dongdong Hao, Yisong Lv, Qiegen Liu, Yueqi Zhu, Song Ding, Jun Zhao, Baowei Fei
PATTERN RECOGNITION
(2019)
Article
Computer Science, Artificial Intelligence
Wenzhao Zhao, Qiegen Liu, Yisong Lv, Binjie Qin
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2019)
Article
Computer Science, Artificial Intelligence
Dongdong Hao, Song Ding, Linwei Qiu, Yisong Lv, Baowei Fei, Yueqi Zhu, Binjie Qin
Article
Clinical Neurology
Geng Zhou, Jienan Wang, Weidong Liu, Wenquan Gu, Ming Su, Yong Feng, Binjie Qin, Yueqi Zhu
BRITISH JOURNAL OF NEUROSURGERY
(2020)
Editorial Material
Neurosciences
Binjie Qin, Sung-Liang Chen, Peng Miao, Zhongzhao Teng
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Binjie Qin, Haohao Mao, Yiming Liu, Jun Zhao, Yisong Lv, Yueqi Zhu, Song Ding, Xu Chen
Summary: In this study, a novel robust PCA unrolling network with sparse feature selection is proposed for super-resolution XCA vessel imaging. The network is embedded within a patch-wise spatiotemporal super-resolution framework and can gradually prune complex vessel-like artefacts and noisy backgrounds in XCA. It can also iteratively learn and select the high-level spatiotemporal semantic information of moving contrast agents flowing in the XCA-imaged vessels. The experimental results show that the proposed method significantly outperforms state-of-the-art methods in imaging the vessel network and its distal vessels.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Engineering, Electrical & Electronic
Yiming Liu, Binjie Qin, Rong Li, Xintong Li, Anqi Huang, Haifeng Liu, Yisong Lv, Min Liu
Summary: This article introduces a novel multimodal quasi-contactless HR sensor that combines face and head motion disturbances and fuses rPPG and BCG signals for accurate heart rate estimation. Experimental comparisons demonstrate that the proposed sensor is more robust and accurate than the state-of-the-art single-modal sensors for heart rate estimation.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Fengqin Zhang, Minghui Zhang, Binjie Qin, Yi Zhang, Zichen Xu, Dong Liang, Qiegen Liu
Summary: The paper introduces a robust enhancement mechanism for sparse-view computed tomography reconstruction, using denoising autoencoding prior method, which can substantially improve the reconstruction quality.
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
(2021)
Proceedings Paper
Automation & Control Systems
Chuan Geng, Qiang Xie, Long Chen, Alex Li, Binjie Qin
PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020)
(2020)
Article
Computer Science, Artificial Intelligence
Kunqiang Mei, Bin Hu, Baowei Fei, Binjie Qin
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2020)
Proceedings Paper
Optics
Kunqiang Mei, Dongdong Hao, Binjie Qin
ELEVENTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2019)
(2019)
Proceedings Paper
Optics
Dongdong Hao, Yiming Liu, Binjie Qin
ELEVENTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2019)
(2019)