Filters








1,037 Hits in 3.0 sec

A Novel Approach for Biofilm Detection Based On a Convolutional Neural Network

Giovanni Dimauro, Francesca Deperte, Rosalia Maglietta, Mario Bove, Fabio La La Gioia, Vito Renò, Lorenzo Simone, Matteo Gelardi
2020 Electronics  
Rhinology studies anatomy, physiology and diseases affecting the nasal region: one of the most modern techniques to diagnose these diseases is nasal cytology or rhinocytology, which involves analyzing  ...  To demonstrate the reliability of the system, alternative solutions based on isolation forest and deep random forest techniques were also tested.  ...  One of the most common diagnostic techniques for identifying rhinological diseases is a nasal cytology, that is the study of nasal cellularity [36] .  ... 
doi:10.3390/electronics9060881 fatcat:6h2ybsgmkbcezpuuu4yakzbv7u

Comparative Analysis of Rhino-Cytological Specimens with Image Analysis and Deep Learning Techniques

Giovanni Dimauro, Vitoantonio Bevilacqua, Pio Raffaele Fina, Domenico Buongiorno, Antonio Brunetti, Sergio Latrofa, Michele Cassano, Matteo Gelardi
2020 Electronics  
Nowadays, the automated detection and classification of cells benefit from the capacity of deep learning techniques in processing digital images of the cytological preparation.  ...  Cytological study of the nasal mucosa (also known as rhino-cytology) represents an important diagnostic aid that allows highlighting of the presence of some types of rhinitis through the analysis of cellular  ...  Deep Learning Deep learning (DL) is a branch of machine learning that consists of a set of techniques and algorithms inspired by human brain processes.  ... 
doi:10.3390/electronics9060952 fatcat:r4rpqiai5ndrpiabdmknkly5ja

Bioelectronic Technologies and Artificial Intelligence for Medical Diagnosis and Healthcare

Giovanni Dimauro, Vitoantonio Bevilacqua, Leandro Pecchia
2021 Electronics  
Deep learning techniques are very promising for the segmentation of glomeruli, with a variety of existing approaches.  ...  The simplicity of the technique makes nasal cytology a practical diagnostic tool for all rhino-allergology services.  ... 
doi:10.3390/electronics10111242 fatcat:m6yjls4arzbbbmydzsbg77bz2q

Deep Learning for Computational Cytology: A Survey [article]

Hao Jiang, Yanning Zhou, Yi Lin, Ronald CK Chan, Jiang Liu, Hao Chen
2022 arXiv   pre-print
We first introduce various deep learning methods, including fully supervised, weakly supervised, unsupervised, and transfer learning.  ...  Recently, an increasing number of deep learning (DL) algorithms have made significant progress in medical image analysis, leading to the boosting publications of cytological studies.  ...  Deep learning in cytology application In this section, we survey and summarize literatures on various deep learning models applied in computational cytology.  ... 
arXiv:2202.05126v2 fatcat:d5ockk4ofjgv3oyxnuce4hmxpu

Manifestations of Tuberculosis in Ear, Nose, Throat, Head and Neck Region – A Retrospective Study

Vandana P Thorawade, S A Jaiswal, Seema Ramlakhan Gupta
2020 Bengal Journal of Otolaryngology and Head Neck Surgery  
This study was done to learn the clinical presentation of tuberculosis in ear, nose, throat and head and neck region, and to assess the effectiveness of various investigations and treatment done for the  ...  Most common site was cervical lymph nodes(77.5% patients), followed by larynx(8.3%),middle ear(7.5%),deep neck spaces(2.5%) and salivary glands and nose(1.7% each).  ...  Deep neck space tuberculosis patients (3 patients) came with complaints of dysphagia and neck pain and TB was diagnosed by microbiological and cytological examinations of the aspirated pus.  ... 
doi:10.47210/bjohns.2020.v28i2.332 doaj:2866200c9715483fbe77ba46ad199fe3 fatcat:evmmrromkff2nbmpt2bohiv4se

Application of Machine Learning in Rhinology: A State of the Art Review

Myeong Sang Yu
2020 Korean Journal of Otorhinolaryngology - Head and Neck Surgery  
Recently, the deep learning techniques including convolutional neural network have been considered as a promising machine learning technique in medical imaging applications.  ...  Machine learning techniques can deal with the complexity of big data which is difficult to apply traditional statistics.  ...  Recently, the deep learning techniques including convolutional neural network have been considered as a promising machine learning technique in medical imaging applications.  ... 
doi:10.3342/kjorl-hns.2020.00633 fatcat:k3n4z3prpbb2zobydjosjmge5a

Cytology Image Analysis Techniques Towards Automation: Systematically Revisited [article]

Shyamali Mitra, Nibaran Das, Soumyajyoti Dey, Sukanta Chakrabarty, Mita Nasipuri, Mrinal Kanti Naskar
2020 arXiv   pre-print
Automation in cytology started in the early 1950s with the aim to reduce manual efforts in diagnosis of cancer.  ...  The inflush of intelligent technological units with high computational power and improved specimen collection techniques helped to achieve its technological heights.  ...  Deep Learning based: Deep learning based framework is one of the latest trends in many applications and being extensively used in segmentation of cytology images. Song et al.  ... 
arXiv:2003.07529v1 fatcat:eossjujftzflbfnfhbsw55tlta

A Smartphone-Based Cell Segmentation to Support Nasal Cytology

Giovanni Dimauro, Davide Di Pierro, Francesca Deperte, Lorenzo Simone, Pio Raffaele Fina
2020 Applied Sciences  
Rhinology studies the anatomy, physiology, and diseases affecting the nasal region—one of the most modern techniques to diagnose these diseases is nasal cytology, which involves microscopic analysis of  ...  the cells contained in the nasal mucosa.  ...  Machine learning developers focus on designing models with a reduced number of parameters in the Deep Neural Network model, thus reducing memory and execution latency, while aiming to preserve accuracy  ... 
doi:10.3390/app10134567 fatcat:vedn4fnl2zb6nnd6r3awcw4fle

A young boy with a maxillary swelling and closed rhinolalia

S. Thomas, P. Nair, A. Kumar, K. Hegde, V. Singh
2011 BMJ Case Reports  
The extranodal, extralymphatic category includes all NHL not in nodes or Waldeyer's ring with the major areas of involvement including the orbit, sinus, nose, mandible, deep facial spaces, parotid gland  ...  in lymphoma, immunohistochemistry and molecular studies being supplementary techniques. 12 High-grade lymphomas are associated with a 60% mortality at 5 years after diagnosis and treatment. 10 A review  ... 
doi:10.1136/bcr.08.2010.3234 pmid:22715226 pmcid:PMC3029663 fatcat:5vvwqp72cvfa5cshqtd4p6oxdm

Part I. Allergy in otolaryngology

French K. Hansel
1948 The Laryngoscope  
One can learn only by individual experience how to evaluate the cytology.  ...  THE CYTOLOGY OF THE NASAL AND SINUS SECRETIONS.  ... 
doi:10.1288/00005537-194807000-00004 pmid:18874379 fatcat:hflqsdkyzjeqzpt6txaljqkdpm

PTU-056 Highly Successful, Minimally Invasive Enteral Access By Double-balloon Enteroscopy (dbe) And Laparoscopic-assisted Dbe

TC Shepherd, O Epstein, A Khan, ET Pring, M Varcada, S Rahman, EJ Despott
2014 Gut  
The overall dysplasia and malignancy rate in the trans nasal group versus the oral group was 2.2% vs. 2.4% (p = 0.4048).  ...  All endoscopists take quadrantic biopsies of the Barrett's segment in accordance with the BSG guidelines.  ...  Conclusion The PMCB technique is a simple, reliable and costeffective EUS-FNA sample preparation technique that in our hands appears superior to conventional cytology preparations (83% diagnostic rate  ... 
doi:10.1136/gutjnl-2014-307263.130 fatcat:kpgrbgj6kjbvtd4hofxocwrvfa

Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery

Bayu Adhi Tama, Do Hyun Kim, Gyuwon Kim, Seungchul Lee, Soo Whan Kim
2020 Clinical and Experimental Otorhinolaryngology  
Machine and deep learning have been extensively applied in the field of otorhinolaryngology. However, performance varies and research challenges remain.  ...  To present an up-to-date survey of the use of artificial intelligence (AI) in the field of otorhinolaryngology, with respect to opportunities, research challenges, and research directions.Methods.  ...  MACHINE LEARNING AND DEEP LEARNING AI has fascinated medical researchers and practitioners since the advent of machine learning (ML) and deep learning (DL) (two forms of AI) in 1990 and 2010, respectively  ... 
doi:10.21053/ceo.2020.00654 pmid:32631041 fatcat:o2qye2o3tvd4hctbkxdd5j53jq

Exfoliative-cell diagnosis of central nervous system lesions

W R PLATT
1951 A M A Archives of Neurology & Psychiatry  
with the para- nasal sinuses in that region.  ...  The nasal fluid on May 25 was clear and colorless, with 2 lymphocytes per cubic millimeter and a sugar content of 72 mg. per 100 cc.; on May 26, the nasal fluid (2 cc.) was turbid and colorless with a  ... 
pmid:14846438 fatcat:ytjfw6l7snbhpfkqw3pzp2cxca

Proceedings of the 145th Semon Club, 23 May 2013, ENT Department, Guy's and St Thomas' NHS Foundation Trust, London, UK

Elfy B Chevretton, Sherif Haikel, Ann Sandison, Ata Siddiqui
2014 Journal of Laryngology and Otology  
This technique can be used to treat conditions such as Crohn's disease.  ...  Cytology findings Fine needle aspiration cytology revealed numerous mononuclear dendritic cells (lesional), with small lymphocytes and large multinucleate osteoclast-like giant cells (nonlesional), consistent  ...  Patients usually present with symptoms secondary to bone marrow failure. Head and neck manifestations of this disease are rarely reported.  ... 
doi:10.1017/s0022215114001108 fatcat:5qca6phkmbce3fy45zjvezry5e

Fast Pre-Diagnosis of Neoplastic Changes in Cytology Images Using Machine Learning

Jakub Caputa, Daria Łukasik, Maciej Wielgosz, Michał Karwatowski, Rafał Frączek, Paweł Russek, Kazimierz Wiatr
2021 Applied Sciences  
A rich dataset of 1219 smeared sample images with 28,149 objects was gathered and annotated by the vet doctor to perform the experiments.  ...  We present the experiment results to use the YOLOv3 neural network architecture to automatically detect tumor cells in cytological samples taken from the skin in canines.  ...  convolutional neural network classification CNN accuracy 83% [4] Nasal cytology with deep learning techniques classification CNN accuracy 94% [5] Automated Classification of Lung Cancer  ... 
doi:10.3390/app11167181 fatcat:houtwfg7vbc6lkml2h5swrqwwq
« Previous Showing results 1 — 15 out of 1,037 results