40 research outputs found
ΠΠ½Π°Π»ΠΈΠ· ΠΈ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ° ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΈΠ±ΡΠΎΠ·Π° Π»Π΅Π³ΠΊΠΈΡ Ρ ΡΠ»ΡΡΡΠ΅Π½Π½ΡΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ Π³Π»ΡΠ±ΠΎΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ
Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΈ ΠΌΡΠΊΠΎΠ²ΠΈΡΡΠΈΠ΄ΠΎΠ·. ΠΡΠ½ΠΎΠ²ΠΎΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ PSPNet Ρ ΠΏΠΎΡΠ΅ΡΠ΅ΠΉ ΠΎΡΠ°Π³Π°, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π²Π²ΠΎΠ΄ΠΈΡΡ Π½Π°Π±ΠΎΡΡ Π΄Π°Π½Π½ΡΡ
Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΈΡ
ΡΡ
ΠΎΠ΄ΡΡΠ²ΠΎΠΌ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΌΡΠΊΠΎΠ²ΠΈΡΡΠΈΠ΄ΠΎΠ· Π»Π΅Π³ΠΊΠΈΡ
. ΠΡΠΎΡΡΠ°Ρ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Π°Ρ ΡΡΡΡΠΊΡΡΡΠ° Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅Ρ ΠΌΠ΅ΡΠΎΠ΄ Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΊΠΈ Π°Π½Π½ΠΎΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ, ΠΊΠΎΡΠΎΡΡΠ΅ Π·Π°ΡΠ΅ΠΌ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΡΡ Π² CNN, ΡΡΠΎ ΠΏΠΎΠΌΠΎΠ³Π°Π΅Ρ Ρ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΠΎΡΠ½ΠΎΡΡΡΡ Π»ΠΎΠΊΠ°Π»ΠΈΠ·ΠΎΠ²Π°ΡΡ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΡΠΊΠΎΠ²ΠΈΡΡΠΈΠ΄ΠΎΠ· Π² Π»Π΅Π³ΠΊΠΈΡ
Diagnostic of Cystic Fibrosis in Lung Computer Tomographic Images using Image Annotation and Improved PSPNet Modelling
The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathological diagnostic signs. The simple and effective algorithm structure groups annotated images, processes them in a multiscale CNN, and localizes areas of cystic fibrosis in the lungs with high accuracy
Towards using Cough for Respiratory Disease Diagnosis by leveraging Artificial Intelligence: A Survey
Cough acoustics contain multitudes of vital information about
pathomorphological alterations in the respiratory system. Reliable and accurate
detection of cough events by investigating the underlying cough latent features
and disease diagnosis can play an indispensable role in revitalizing the
healthcare practices. The recent application of Artificial Intelligence (AI)
and advances of ubiquitous computing for respiratory disease prediction has
created an auspicious trend and myriad of future possibilities in the medical
domain. In particular, there is an expeditiously emerging trend of Machine
learning (ML) and Deep Learning (DL)-based diagnostic algorithms exploiting
cough signatures. The enormous body of literature on cough-based AI algorithms
demonstrate that these models can play a significant role for detecting the
onset of a specific respiratory disease. However, it is pertinent to collect
the information from all relevant studies in an exhaustive manner for the
medical experts and AI scientists to analyze the decisive role of AI/ML. This
survey offers a comprehensive overview of the cough data-driven ML/DL detection
and preliminary diagnosis frameworks, along with a detailed list of significant
features. We investigate the mechanism that causes cough and the latent cough
features of the respiratory modalities. We also analyze the customized cough
monitoring application, and their AI-powered recognition algorithms. Challenges
and prospective future research directions to develop practical, robust, and
ubiquitous solutions are also discussed in detail.Comment: 30 pages, 12 figures, 9 table
PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques
Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single-valued population-based lung LAC, and better estimation is needed to improve quantification. Given the under-appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single-valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission-based schemes. Potential strategies for future developments are also presented
Diseases of the Chest, Breast, Heart and Vessels 2019-2022
This open access book focuses on diagnostic and interventional imaging of the chest, breast, heart, and vessels. It consists of a remarkable collection of contributions authored by internationally respected experts, featuring the most recent diagnostic developments and technological advances with a highly didactical approach. The chapters are disease-oriented and cover all the relevant imaging modalities, including standard radiography, CT, nuclear medicine with PET, ultrasound and magnetic resonance imaging, as well as imaging-guided interventions. As such, it presents a comprehensive review of current knowledge on imaging of the heart and chest, as well as thoracic interventions and a selection of "hot topics". The book is intended for radiologists, however, it is also of interest to clinicians in oncology, cardiology, and pulmonology
Diseases of the Chest, Breast, Heart and Vessels 2019-2022
This open access book focuses on diagnostic and interventional imaging of the chest, breast, heart, and vessels. It consists of a remarkable collection of contributions authored by internationally respected experts, featuring the most recent diagnostic developments and technological advances with a highly didactical approach. The chapters are disease-oriented and cover all the relevant imaging modalities, including standard radiography, CT, nuclear medicine with PET, ultrasound and magnetic resonance imaging, as well as imaging-guided interventions. As such, it presents a comprehensive review of current knowledge on imaging of the heart and chest, as well as thoracic interventions and a selection of "hot topics". The book is intended for radiologists, however, it is also of interest to clinicians in oncology, cardiology, and pulmonology