Results 41 to 50 of about 29,416,981 (354)

Medical imaging [PDF]

Postgraduate Medical Journal, 1991
Summary and conclusionsThere is now a wide choice of medical imaging to show both focal and diffuse pathologies in various organs. Conventional radiology with plain films, fluoroscopy and contrast medium have many advantages, being readily available with low-cost apparatus and a familiarity that almost leads to contempt. The use of plain films in chest
openaire   +2 more sources

Cervical Histopathology Image Classification Using Multilayer Hidden Conditional Random Fields and Weakly Supervised Learning

IEEE Access, 2019
In this paper, a novel multilayer hidden conditional random fields (MHCRFs)-based cervical histopathology image classification (CHIC) model is proposed to classify well, moderate and poorly differentiation stages of cervical cancer using a weakly ...
Chen Li, Hao Chen, Le Zhang, Ning Xu, Dan Xue, Zhijie Hu, He Ma, Hongzan Sun   +7 more
doaj   +1 more source

Mn doped Prussian blue nanoparticles for T1/T2 MR imaging, PA imaging and Fenton reaction enhanced mild temperature photothermal therapy of tumor

Journal of Nanobiotechnology, 2022
Background Combining the multimodal imaging and synergistic treatment in one platform can enhance the therapeutic efficacy and diagnosis accuracy. Results In this contribution, innovative Mn-doped Prussian blue nanoparticles (MnPB NPs) were prepared via ...
Quan Tao, Genghan He, Sheng Ye, Di Zhang, Zhide Zhang, Li Qi, Ruiyuan Liu   +6 more
doaj   +1 more source

Robust and Imperceptible Watermarking on Medical Images using Coefficient Pair Modification

International Islamic University Malaysia Engineering Journal, 2023
Sensitive data including medical images and electronic patient records (EPR) have potential value in the era of big data and telemedicine applications.
Ledya Novamizanti, Andriyan Bayu Suksmono, Donny Danudirdjo, Gelar Budiman   +3 more
doaj   +1 more source

VM-UNet: Vision Mamba UNet for Medical Image Segmentation [PDF]

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
In the realm of medical image segmentation, both CNN-based and Transformer-based models have been extensively explored. However, CNNs exhibit limitations in long-range modeling capabilities, whereas Transformers are hampered by their quadratic ...
Jiacheng Ruan, Jincheng Li, Sun-Cheng Xiang   +2 more
semanticscholar   +1 more source

Clinical and MRI Features of Tumors of Septum Pellucidum

Zhongliu Fangzhi Yanjiu, 2018
Objective To investigate the clinical and magnetic resonance imaging (MRI) features of the tumors of septum pellucidum. Methods We analyzed retrospectively the clinical data of 45 patients with the tumors of septum pellucidum confirmed by operation and ...
HAO Ni'na, JIN Song, HAN Tong, LI Li, CUI Shimin   +4 more
doaj   +1 more source

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

bioRxiv, 2019
MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI.
Jacques-Donald Tournier, R. Smith, D. Raffelt, R. Tabbara, Thijs Dhollander, Maximilian Pietsch, D. Christiaens, B. Jeurissen, Chun-Hung Yeh, A. Connelly   +9 more
semanticscholar   +1 more source

A State-of-the-Art Survey for Microorganism Image Segmentation Methods and Future Potential

IEEE Access, 2019
Microorganisms play a great role in ecosystem, wastewater treatment, monitoring of environmental changes, and decomposition of waste materials. However, some of them are harmful to humans and animals such as tuberculosis bacteria and plasmodium.
Frank Kulwa, Chen Li, Xin Zhao, Bencheng Cai, Ning Xu, Shouliang Qi, Shuo Chen, Yueyang Teng   +7 more
doaj   +1 more source

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

European Radiology Experimental, 2020
Background Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on different datasets ...
Johannes Hofmanninger, Forian Prayer, Jeanny Pan, Sebastian Röhrich, Helmut Prosch, Georg Langs   +5 more
doaj   +1 more source

UniverSeg: Universal Medical Image Segmentation [PDF]

IEEE International Conference on Computer Vision, 2023
While deep learning models have become the predominant method for medical image segmentation, they are typically not capable of generalizing to unseen segmentation tasks involving new anatomies, image modalities, or labels. Given a new segmentation task,
V. Butoi, Jose Javier Gonzalez Ortiz, Tianyu Ma, M. Sabuncu, J. Guttag, Adrian V. Dalca   +5 more
semanticscholar   +1 more source