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A. M. Beznarytnyy,V. I. Gavrilyuk
Pág. 7 - 15
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Domantas Kuzinkovas and Sandhya Clement
Advances in the field of image classification using convolutional neural networks (CNNs) have greatly improved the accuracy of medical image diagnosis by radiologists. Numerous research groups have applied CNN methods to diagnose respiratory illnesses fr...
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May Phu Paing, Kazuhiko Hamamoto, Supan Tungjitkusolmun and Chuchart Pintavirooj
Lung cancer is a life-threatening disease with the highest morbidity and mortality rates of any cancer worldwide. Clinical staging of lung cancer can significantly reduce the mortality rate, because effective treatment options strongly depend on the spec...
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Arun Kumar Sangaiah, Samira Rezaei, Amir Javadpour, Farimasadat Miri, Weizhe Zhang and Desheng Wang
Handling faults in a running cellular network can impair the performance and dissatisfy the end users. It is important to design an automatic self-healing procedure to not only detect the active faults, but also to diagnosis them automatically. Although ...
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Anis Malekzadeh, Assef Zare, Mahdi Yaghoobi and Roohallah Alizadehsani
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension (FD) and a deep learning (DL) model. Firstly, Bonn and Freiburg datasets were used to perform exp...
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Rosa Senatore, Antonio Della Cioppa and Angelo Marcelli
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Rosa Senatore, Antonio Della Cioppa and Angelo Marcelli
Background: The use of Artificial Intelligence (AI) systems for automatic diagnoses is increasingly in the clinical field, being a useful support for the identification of several diseases. Nonetheless, the acceptance of AI-based diagnoses by the physici...
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Alexander P. Seiffert, Adolfo Gómez-Grande, Patrick Pilkington, Paula Cara, Héctor Bueno, Juana Estenoz, Enrique J. Gómez and Patricia Sánchez-González
Chronic thromboembolic pulmonary hypertension (CTEPH) is confirmed by visual analysis of single-photon emission computer tomography (SPECT) ventilation and perfusion (V/Q) images. Defects in the perfusion image discordant with the ventilation image indic...
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Bhagya Nathali Silva, Murad Khan, Ruchire Eranga Wijesinghe, Samantha Thelijjagoda and Kijun Han
Survivors of either a hemorrhagic or ischemic stroke tend to acquire aphasia and experience spontaneous recovery during the first six months. Nevertheless, a considerable number of patients sustain aphasia and require speech and language therapy to overc...
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Delia Alexandrina Mitrea,Sergiu Nedevschi,Mihail Abrudean,Radu Chifor,Radu Badea
Pág. 61 - 67
The non-invasive diagnosis, based on ultrasound images, is a challenge in nowadays research. We develop computerized, texture-based methods, for automatic and computer assisted diagnosis, using the information obtained from ultrasound images. In this wor...
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Lin Lin, Xuri Chen, Ying Shen and Lin Zhang
The proposed automatic depression detection method aims at: (1) supporting clinical diagnosis with objective and quantitative measurements and (2) providing a quick, effective, and economic self depressive assessment.
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Chuanbo Wang, Amirreza Mahbod, Isabella Ellinger, Adrian Galdran, Sandeep Gopalakrishnan, Jeffrey Niezgoda and Zeyun Yu
Wound care professionals provide proper diagnosis and treatment with heavy reliance on images and image documentation. Segmentation of wound boundaries in images is a key component of the care and diagnosis protocol since it is important to estimate the ...
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Jianhang Zhou, Qi Zhang, Bob Zhang and Xiaojiao Chen
Automated tongue segmentation is a critical component of tongue diagnosis, especially in Traditional Chinese Medicine (TCM), where it has been practiced for thousands of years and is generally considered pain-free and non-invasive. Therefore, a more prec...
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Yu Tang, Zhiqin He, Qinmu Wu, Xiao Wang and Yuhang Wang
The scoliosis report is a diagnosis made by the clinician looking at X-ray images of the spine. However, with numerous images, writing the report can be time-consuming and error-prone. Therefore, this paper proposes an automatic generation model of the e...
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Wei Xiao, Mingxia Liu and Xubing Chen
The underground intelligent load-haul-dump vehicle (LHD) is a product of the deep integration of traditional LHD with information network technology, automatic controlling and artificial intelligence technology. It gathers the functions of environmental ...
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Hanguang Xiao, Yuewei Li, Bin Jiang, Qingling Xia, Yujia Wei and Huanqi Li
Lung cancer is the highest-mortality cancer with the largest number of patients in the world. Early screening and diagnosis of lung cancer by CT imaging is of great significance to improve the cure rate of lung cancer. CT signs mean the information of co...
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Ilaria Bartolini and Andrea Di Luzio
Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). A recent approach for the diagnosis of the disease is based on a completely manual analys...
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Nadia Brancati and Maria Frucci
To support pathologists in breast tumor diagnosis, deep learning plays a crucial role in the development of histological whole slide image (WSI) classification methods. However, automatic classification is challenging due to the high-resolution data and ...
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Jin-Woo Kong, Byoung-Doo Oh, Chulho Kim and Yu-Seop Kim
Intracerebral hemorrhage (ICH) is a severe cerebrovascular disorder that poses a life-threatening risk, necessitating swift diagnosis and treatment. While CT scans are the most effective diagnostic tool for detecting cerebral hemorrhage, their interpreta...
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Giulia Rubiu, Marco Bologna, Michaela Cellina, Maurizio Cè, Davide Sala, Roberto Pagani, Elisa Mattavelli, Deborah Fazzini, Simona Ibba, Sergio Papa and Marco Alì
Convolutional Neural Network (CNN) models are capable of learning complex patterns and features from images. An automatic teeth segmentation CNN model can accurately and efficiently identify the boundaries and contours of individual teeth in dental radio...
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