Search · four archives
Search · four archives
20 papers · ranked by Valyu relevance
Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Anan Li + 7 more
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning based methods demand huge training data and are…
Bin Duan, Logan A Walker, Bin Xie, Wei Jie Lee + 3 more
Recent advances in microscopy have pushed imaging data generation to an unprecedented scale. While scientists benefit from higher spatiotemporal resolutions and larger imaging volumes, the increasing data size presents significant storage, visualization, sharing, and analysis challenges. Lossless compression typically…
Abdul Khader Jilani Saudagar
The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural networks in order to…
Asif Shahriyar Sushmit, Shakib Uz Zaman, Ahmed Imtiaz Humayun, Taufiq Hasan + 1 more
'Taufiq Hasan' 'Mohammed Imamul Hassan Bhuiyan'] Abstract—In the advent of a digital health revolution, vast amounts of clinical data are being generated, stored and processed on a daily basis. This has made the storage and retrieval of large volumes of health-care data, especially, highresolution medical images…
Bas Hulsken
T he need for fast diagnostic image viewing in zero footprint web applications and the ever increasing image sizes for new modalities such as digital pathology have painfully brought to light that the currently available image compression methods fall short. JPEG2000 delivers the image quality required for medical…
Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Qianni Cao + 3 more
'Jinli Suo' 'Qionghai Dai'] Massive collection and explosive growth of biomedical data, demands effective compression for efficient storage, transmission and sharing. Readily available visual data compression techniques have been studied extensively but tailored for natural images/videos, and thus show limited…
Yifan Ma, Chengqiang Yi, Yao Zhou, Zhaofei Wang + 9 more
With the rapid development in advanced imaging techniques, massive image data have been acquired for various biomedical applications, posing significant challenges to their efficient storage, transmission, and sharing. Classical model-or learning-based compression algorithms are optimized for specific dimensional data…
Utkarsh Prakash Srivastava, Toshiaki Fujii
The vast volume of medical image data necessitates efficient compression techniques to support remote healthcare services. This paper explores Region of Interest (ROI) coding to address the balance between compression rate and image quality. By leveraging UNET segmentation on the Brats 2020 dataset, we accurately…
Babajide O. Ayinde
Near-lossless image compression-decompression scheme is proposed in this paper using Zipper Transformation (ZT) and inverse zipper transformation (iZT). The proposed ZT exploits the conjugate symmetry property of Discrete Fourier Transformation (DFT). The proposed transformation is implemented using two different…
Kevin Christopher VanHorn, Murat Can Çobanoğlu
Region extraction is necessary in a wide range of applications, from object detection in autonomous driving to analysis of subcellular morphology in cell biology. There exist two main approaches: convex hull extraction, for which exact and efficient algorithms exist and concave hulls, which are better at capturing…
Yaghoub Pourasad, Fausto Cavallaro, Paul B. Tchounwou
At present, there is an increase in the capacity of data generated and stored in the medical area. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. To reduce the redundancy of the contents of the image, thus increasing…
Suraj Mishra, Danny Z. Chen, Xiaobo Sharon Hu
Compression is a standard procedure for making convolutional neural networks (CNNs) adhere to some specific computing resource constraints. However, searching for a compressed architecture typically involves a series of time-consuming training/validation experiments to determine a good compromise between network size…
Yen-Wei Chen, Ikuko Nishikawa, Shinichi Tamura, Bao-Liang Lu + 1 more
'Huiyan Jiang'] Biomedical science and engineering is an interdisciplinary research field, which combines the advanced technologies and problem solving skills with medical and biological science. Since the biomedical solutions generally have large variations and complexity, it is difficult to use a simple way or a…
Song Jiang, Ela Kumar
Enormous data permeates various facets of social life, including public administration, community services, and scientific research, owing to the advent of new technologies. With the escalation of data transportation concerns, its significance in our daily lives has magnified. Particularly in the medical field…
Samuel Cahyawijaya
Biomedical image reconstruction research has been developed for more than five decades, giving rise to various techniques such as central and filtered back projection. With the rise of deep learning technology, biomedical image reconstruction field has undergone a massive paradigm shift from analytical and iterative…
Hongyang Dong, Simon D.M. Jacques, Winfried Kockelmann, Stephen W. T. Price + 10 more
Hongyang Dong 3 , Simon D.M. Jacques 1 , Winfried Kockelmann 4 , Stephen W. T. Price 1 , Robert Emberson 5 , Dorota Matras 6,7 , Yaroslav Odarchenko 1 , Vesna Middelkoop 10 , Athanasios Giokaris 1 , Olof Gutowski 8 , Ann-Christin Dippel 8 , Martin v. Zimmermann 8 , Andrew M. Beale 3 , Keith T. Butler 9 , Antonis…
Anke Meyer-Baese, Claudia Plant, Juan Manuel Gorriz Saez
Medical imaging is today becoming one of the most important visualization and interpretation methods in biology and medicine. The past decade has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying images. These instruments are greatly…
Edward J Ciaccio
This article is a review of the book: 'Biomedical Image Processing', by Thomas M. Deserno, which is published by Springer-Verlag. Salient information that will be useful to decide whether the book is relevant to topics of interest to the reader, and whether it might be suitable as a course textbook, are presented in…
Yi-Hong Lin, Chih-Ning Tsai, Po-Feng Chen, Yen-Tzu Lin + 5 more
Scanning electrochemical microscopy (SECM) is one of the scanning probe techniques that has attracted considerable attention because of its ability to interrogate surface morphology or electrochemical reactivity. However, the quality of SECM images generally depends on the sizes of the electrodes and many…
Daniel Probst
Last year, a preprint gained notoriety, proposing that a k-nearest neighbour classifier is able to outperform large-language models using compressed text as input and normalised compression distance (NCD) as a metric. In chemistry and biochemistry, molecules are often represented as strings, such as SMILES for small…