scholarly journals Per-COVID-19: A Benchmark Dataset for COVID-19 Percentage Estimation from CT-Scans

2021 ◽  
Vol 7 (9) ◽  
pp. 189
Author(s):  
Fares Bougourzi ◽  
Cosimo Distante ◽  
Abdelkrim Ouafi ◽  
Fadi Dornaika ◽  
Abdenour Hadid ◽  
...  
Keyword(s):  
Mean Absolute Error ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Ct Scans ◽  
Rt Pcr ◽  
X Ray ◽  
Fast Solution ◽  
Patient State ◽  
Polymerase Chain ◽  
Tomography Scan

COVID-19 infection recognition is a very important step in the fight against the COVID-19 pandemic. In fact, many methods have been used to recognize COVID-19 infection including Reverse Transcription Polymerase Chain Reaction (RT-PCR), X-ray scan, and Computed Tomography scan (CT- scan). In addition to the recognition of the COVID-19 infection, CT scans can provide more important information about the evolution of this disease and its severity. With the extensive number of COVID-19 infections, estimating the COVID-19 percentage can help the intensive care to free up the resuscitation beds for the critical cases and follow other protocol for less severity cases. In this paper, we introduce COVID-19 percentage estimation dataset from CT-scans, where the labeling process was accomplished by two expert radiologists. Moreover, we evaluate the performance of three Convolutional Neural Network (CNN) architectures: ResneXt-50, Densenet-161, and Inception-v3. For the three CNN architectures, we use two loss functions: MSE and Dynamic Huber. In addition, two pretrained scenarios are investigated (ImageNet pretrained models and pretrained models using X-ray data). The evaluated approaches achieved promising results on the estimation of COVID-19 infection. Inception-v3 using Dynamic Huber loss function and pretrained models using X-ray data achieved the best performance for slice-level results: 0.9365, 5.10, and 9.25 for Pearson Correlation coefficient (PC), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE), respectively. On the other hand, the same approach achieved 0.9603, 4.01, and 6.79 for PCsubj, MAEsubj, and RMSEsubj, respectively, for subject-level results. These results prove that using CNN architectures can provide accurate and fast solution to estimate the COVID-19 infection percentage for monitoring the evolution of the patient state.

scholarly journals Per-Covid-19: A Benchmark Database For Covid-19 Percentage Prediction From CT-scans

2021 ◽  
Author(s):  
Fares Bougourzi ◽  
Cosimo Distante ◽  
Ouafi Abdelkrim ◽  
Fadi Dornaika ◽  
Abdenour Hadid ◽  
...  
Keyword(s):  
Neural Network ◽  
Polymerase Chain Reaction ◽  
Intensive Care ◽  
Loss Functions ◽  
Ct Scans ◽  
Rt Pcr ◽  
Chain Reaction ◽  
X Ray ◽  
Benchmark Database ◽  
Polymerase Chain

Abstract Covid-19 infection recognition is very important step in the fighting against the new pandemic Covid-19. In fact, many methods have been used to recognize the Covid-19 infection including Reverse transcription polymerase chain reaction (RT-PCR), X-ray scan and CT-scan. In addition to the recognition of the Covid-19 infection, CT-scans can provide more important information about the evolution of this disease and its severity. With the extensive number of Covid-19 infections, estimating the Covid-19 percentage can help the intensive care to free up the resuscitation beds for the critical cases and follow other protocol for less severity cases. In this paper, we propose Covid-19 percentage estimation database. Moreover, we evaluate the performance of three Covolutional Neural Network (CNN) architectures which are ResneXt-50, Densenet-161 and Inception-v3. For the three CNN architectures, we use two loss functions which are MSE and Dynamic Huber. In addition, two pretrained scenarios are investigated (ImageNet pretrained models and X-ray pretrained models). The evaluated approaches achieved promising results, where Inception-v3 with using Dynamic Huber loss function and X-ray pretrained model achieved the best performance.

scholarly journals Chest CT as a Complement to RT-PCR to Confirm and Follow-up COVID-19 Patients

Medicinus ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 31
Author(s):  
Aziza Ghanie Icksan ◽  
Muhammad Hafiz ◽  
Annisa Dian Harlivasari
Keyword(s):  
Chest Ct ◽  
Rt Pcr ◽  
High Resolution Computed Tomography ◽  
X Ray ◽  
First Case ◽  
Chest X Ray ◽  
Polymerase Chain

<p><strong>Background : </strong>The first case of COVID-19 in Indonesia was recorded in March 2020. Limitation of reverse-transcription polymerase chain reaction (RT-PCR) has put chest CT as an essential complementary tool in the diagnosis and follow up treatment for COVID-19. Literatures strongly suggested that High-Resolution Computed Tomography (HRCT) is essential in diagnosing typical symptoms of COVID-19 at the early phase of disease due to its superior sensitivity  (97%) compared to chest x-ray (CXR).</p><p>The two cases presented in this case study showed the crucial role of chest CT with HRCT to establish the working diagnosis and follow up COVID-19 patients as a complement to RT-PCR, currently deemed a gold standard.<strong></strong></p>

scholarly journals Is the Portable Chest Radiographic More Reliable to Reveal Covid19 in Highly Suspicion Patient before Real-Time Reverse Transcription Polymerase Chain Reaction (RT-PCR) Test?

2021 ◽  
Vol 6 (03) ◽  
pp. 228-236
Author(s):  
Bushra A. A. Albazi ◽  
Dr Noof. Albaz ◽  
Dr Nayef. Alqahtani ◽  
Dr. Angham Salih ◽  
Dr Rafat Mohtasab
Keyword(s):  
Polymerase Chain Reaction ◽  
Retrospective Study ◽  
Predictive Value ◽  
Rt Pcr ◽  
Chain Reaction ◽  
X Ray ◽  
Polymerase Chain ◽  
Rate Type ◽  
Test Result ◽  
Pcr Test

A large number of patients with coronavirus disease 2019 (COVID-19) present at hospitals. There are a limited number of isolation rooms open, and patients must often wait a long time to get a reverse transcription-polymerase chain reaction (RT-PCR) test done. This necessitates the introduction of effective triage plans. A patient with suspicions is referred to an emergency room (ED) depending on their medical record for a simple physical assessment, blood test findings, and chest imaging.A retrospective study design was conduct at Prince Sultan Medical Military City (PSMMC). Ethical approval was obtained from the institutional board to wave the consent forms since it is a retrospective study. Only the primary investigator has had the data access to the patients’ medical records. The collected patient records were under specific categories, including symptoms score starts from 5 and above, RT-PCR test result done after CXRP imaging, the patient admitted to the emergency department (ED). Excluding all CXRP done after RT-PCR TEST, positive Covid 19 admitted to the intensive care unit (ICU), pediatric patients, and patients with score symptoms were less than five. Two experienced radiologists reviewed the images blindly, and the inter-observer reliability of observations noted by the radiologists was calculated. As for the relationship between the x-ray reading and the RT-PCR test result, our results showed a high correlation between the variables (chi-square χ² = 12.44, with df =1, and p<0.001). The sensitivity of x-ray diagnosing covid19 was 65.52 %, while the specificity was 54.51 %, and the accuracy of radiologists reading was 58.17 %. Furthermore, the positive predictive value (PPV) was 41.76 %, and the negative predictive value (NPV) was 76.05%. Finally, the false positive rate (type-i error (alpha) was 45.49%, and the false-negative rate (type-ii error (beta) was 34.48% Our research findings show that CXRP imaging can detect COVID-19 infection in symptomatic patients and can be a valuable addition to RT-PCR testing. In an inpatient ED environment where availability of test kits, laboratory equipment, and laboratory personnel is compromised and risks delaying patient treatment and hospital workflow, serial CXRP could theoretically be used as an adjunct diagnostic function and monitoring in patients suspected of having COVID-19.

scholarly journals Current Imaging Trends in COVID-19 Pneumonia

2020 ◽  
Vol 58 (226) ◽  
Author(s):  
Anamika Jha ◽  
Benu Lohani ◽  
Ram Kumar Ghimire
Keyword(s):  
Computed Tomography ◽  
Health Care ◽  
Disease Transmission ◽  
Medical Council ◽  
X Ray ◽  
System Functioning ◽  
Chest X Ray ◽  
Polymerase Chain ◽  
Tomography Scan

COVID-19 has rapidly emerged as a pandemic threatening lives and healthcare systems worldwide.With the emergence of the disease in Nepal, all faculties of medicine need to be well prepared toface the challenge. Fortunately, now plenty of research is available to facilitate our preparednessin the war against COVID-19. The reverse transcriptase-polymerase chain reaction is the currentgold standard diagnostic test and chest Computed Tomography scan for screening the disease isconsidered inappropriate by most society recommendations. The Nepal Radiologists’ Associationhas proposed its guidelines which have been endorsed by the Nepal Medical Council. This articleaims to summarize the role of imaging focusing on chest X-ray and Computed Tomography scanincluding the indications, specific findings, and important differentials. Imaging needs to be donetaking necessary precautions, to minimize disease transmission, protect health care personnel, andpreserve health care system functioning.

scholarly journals Penilaian Esai Pendek Otomatis dengan Pencocokan Kata Kunci Frasa Nomina

Techno Com ◽  
2021 ◽  
Vol 20 (4) ◽  
pp. 489-498
Author(s):  
Nurul Chamidah ◽  
Mayanda Mega Santoni ◽  
Helena Nurramdhani Irmanda ◽  
Ria Astriratma
Keyword(s):  
Mean Absolute Error ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Pos Tagging ◽  
Part Of Speech

Pembelajaran daring menjadi suatu kebutuhan dalam pengajaran baik dalam memberikan materi maupun ujian. Ujian dalam bentuk soal objektif kurang dapat mengukur kemampuan pemahaman seseorang dan soal esai dianggap lebih baik untuk mengevaluasi hasil pembelajaran. Namun, jawaban berbentuk esai memerlukan waktu yang lebih banyak untuk dilakukan penilaian serta hasil penilaiannya dapat inkonsisten. Maka dari itu, diperlukan suatu sistem penilaian esai otomatis yang dapat menilai esai dengan lebih cepat dan konsisten. Penelitian ini dilakukan untuk menganalisis performa penilain esai otomatis dengan mengekstrak kata kunci dari frasa nomina dalam jawaban berbentuk esai pendek. Penilaian esai dilakukan dengan mencocokkan kata kunci yang diekstrak dari jawaban uji dan jawaban referensi. Jawaban uji dan referensi diproses dengan case folding, Part of Speech (POS) Tagging, ekstraksi frasa nomina, dan stemming. Kata kunci unik jawaban uji dan jawaban referensi yang diperoleh dari proses tersebut selanjutnya dicocokkan dan kemudian dinilai berdasarkan kecocokan tersebut. Hasil evaluasi penelitian ini menunjukkan Mean Absolute Error (MAE) dari nilai yang diperoleh dengan mencocokkan kata kunci dengan nilai uji yang diberikan manusia sebesar 18% dan Pearson Correlation sebesar 0.83 yang menunjukkan korelasi antara nilai sistem dan nilai uji sangat baik.

scholarly journals Automatically steering cardiac catheters in vivo with respiratory motion compensation

2020 ◽  
Vol 39 (5) ◽  
pp. 586-597 ◽  
Author(s):  
Paul M Loschak ◽  
Alperen Degirmenci ◽  
Cory M Tschabrunn ◽  
Elad Anter ◽  
Robert D Howe
Keyword(s):  
Motion Compensation ◽  
Respiratory Motion ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Respiratory Motion Compensation ◽  
X Ray ◽  
Cardiac Catheters ◽  
The Us ◽  
Predictive Filtering

A robotic system for automatically navigating ultrasound (US) imaging catheters can provide real-time intra-cardiac imaging for diagnosis and treatment while reducing the need for clinicians to perform manual catheter steering. Clinical deployment of such a system requires accurate navigation despite the presence of disturbances including cyclical physiological motions (e.g., respiration). In this work, we report results from in vivo trials of automatic target tracking using our system, which is the first to navigate cardiac catheters with respiratory motion compensation. The effects of respiratory disturbances on the US catheter are modeled and then applied to four-degree-of-freedom steering kinematics with predictive filtering. This enables the system to accurately steer the US catheter and aim the US imager at a target despite respiratory motion disturbance. In vivo animal respiratory motion compensation results demonstrate automatic US catheter steering to image a target ablation catheter with 1.05 mm and 1.33° mean absolute error. Robotic US catheter steering with motion compensation can improve cardiac catheterization techniques while reducing clinician effort and X-ray exposure.

The Effects of Different Hydroxyapatite/TiO2 Composite Coatings on Protein Expression of Osteoblast

2009 ◽  
Vol 610-613 ◽  
pp. 1104-1108 ◽  
Author(s):  
Jian Ye Han ◽  
Zhen Tao Yu ◽  
Lian Zhou
Keyword(s):  
Protein Expression ◽  
Type I Collagen ◽  
Composite Coatings ◽  
Type I ◽  
X Ray Diffraction ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Compound Formation ◽  
X Ray ◽  
Polymerase Chain

Hydroxyapatite/TiO2 composite material was coated onto Ti25Nb3Mo2Sn3Zr (TLM) alloy substrate. To study the effects of hydroxyapatite/TiO2 composite coatings on bone-related protein expression, the osteoblast were cultured with composite coatings for different times. The phase transformation and compound formation of the HA/TiO2 coatings were investigated using XRD (X-ray diffraction). The mRNA expression of Type I collagen, alkaline phosphatase (ALP) and osteocalcin were studied by RT-PCR (reverse transcriptional polymerase chain reaction). The titania delayed the crystallization of HA. The mRNA expressions of Type I collagen are decreased as the increasing of TiO2 percentage. The mRNA expressions of osteocalcin are approached. The ALP expression on H4 coating (HA/TiO2 mol ration is 5) after the osteoblast cultured with composite coating for 6 days is the highest. The increasing of TiO2 amount decreases the bioactivity of the composite coatings.

scholarly journals Case Report: Extrapulmonary Manifestations of COVID-19 and Dengue Coinfection

2021 ◽  
Author(s):  
José Manuel Reyes-Ruiz ◽  
Rosa Campuzano-Vences ◽  
Juan Fidel Osuna-Ramos ◽  
Luis Adrián De Jesús-González ◽  
María J. Pérez-Méndez ◽  
...  
Keyword(s):  
Clinical Manifestations ◽  
Serum Levels ◽  
Rt Pcr ◽  
Virus Serotype ◽  
Serotype 1 ◽  
Ns1 Antigen ◽  
Control And Prevention ◽  
Normal Chest ◽  
Polymerase Chain ◽  
Tomography Scan

The risk of coronavirus disease 2019 (COVID-19) and dengue coinfection is increased in tropical countries; however, the extrapulmonary clinical manifestations have not been fully characterized. We report a 42-year-old woman whose clinical manifestations began with fever, diarrhea, headache, chest pain, myalgia, odynophagia, and arthralgia. Despite mild respiratory symptoms and normal chest computed tomography scan results, she was diagnosed with real-time reverse-transcription polymerase chain reaction (RT-PCR)-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Because she had erythema and petechiae with a decreased platelet count, the dengue NS1 antigen and anti-dengue IgM/IgG test were performed, and the Centers for Disease Control and Prevention RT-PCR assay detected the dengue virus serotype 1 infection. Additionally, increased liver enzyme serum levels were found in the patient, who later developed hepatomegaly. Hence, the mechanism of hepatic pathology associated with SARS-CoV-2 and dengue coinfection needs further research.

scholarly journals Association of rs7574865 polymorphism of the STAT4 gene with spinal syndesmophytes in patients with ankylosing spondylitis

2021 ◽  
Vol 59 (2) ◽  
pp. 152-157
Author(s):  
M. Yu. Krylov ◽  
Sh. F. Erdes
Keyword(s):  
Lumbar Spine ◽  
Ankylosing Spondylitis ◽  
Thoracic Spine ◽  
Structural Changes ◽  
Disease Duration ◽  
Rt Pcr ◽  
X Ray ◽  
Allele Specific ◽  
Polymerase Chain ◽  
Spearman’S Correlation

Objective. The aim of the investigation was to study the possible association of the rs7574865 polymorphism of the STAT4 gene with syndesmophytes (SMP) of the spine in patients with ankylosing spondylitis (AS).Subjects and methods. The study included a cohort of 100 patients, 79 men and 21 women with a diagnosis of AS.All patients were positive for the HLA-B27 antigen, had a mean age of 39.6±10.9 years and a mean disease duration of 60,4±28,4 months. The association of the rs7574865 polymorphism of the STAT4 gene with the SMP of the cervical, thoracic and lumbar spine was studied. For genotyping of the rs7574865 polymorphism, the method of allele-specific polymerase chain reaction in real time (RT-PCR) was used.Results. Spearman’s correlation analysis showed a statistically significant positive relationship between SMP in the thoracic spine and rs7574865 polymorphism of the STAT4 gene (r=0.23; p=0.022). The frequency of GT genotype carriers in the group of patients with thoracic spine trSMP(+) was statistically significantly lower than in the alternative group trSMP(–) (28.2% and 50.8%, respectively; p=0.025). Carriage of the GT genotype in patients with AS reduced the risk of trSMP(+) formation in the thoracic spine (OR=0.31) and this genotype was protective. No reliably significant association of the studied polymorphism with SMP of the cervical and lumbar spine was found. Patients with trSMP(+) were statistically significantly older in age, had a longer duration of the disease and a higher functional BASFI index compared with patients without trSMP(–).Conclusion. Genetic testing of the rs7574865 G/T polymorphism of the STAT4 gene in patients with AS opens up the possibility of using this polymorphism as a genetic marker-predictor – X-ray progression of structural changes in the thoracic spine.

scholarly journals An approach to categorize chest X-ray images using sparse categorical cross entropy

2021 ◽  
Vol 24 (3) ◽  
pp. 1700
Author(s):  
Chaithanya B. N. ◽  
Swasthika Jain T. J. ◽  
A. Usha Ruby ◽  
Ayesha Parveen
Keyword(s):  
Machine Learning ◽  
Cost Effective ◽  
Cross Entropy ◽  
Ct Scans ◽  
Rt Pcr ◽  
Time Saving ◽  
X Ray ◽  
Proposed Model ◽  
Chest X Ray ◽  
Entropy Technique

The Coronavirus disease (COVID-19) pandemic is the most recent threat to global health. Reverse transcription-polymerase chain reaction (RT-PCR) testing, computed tomography (CT) scans, and chest X-ray (CXR) images are being used to identify Coronavirus, one of the most serious community viruses of the twenty-first century. Because CT scans and RT-PCR analyses are not available in most health divisions, CXR images are typically the most time-saving and cost-effective tool for physicians in making decisions. Artificial intelligence and machine learning have become increasingly popular because of recent technical advancements. The goal of this project is to combine machine learning, deep learning, and the health-care sector to create a categorization technique for detecting the Coronavirus and other respiratory disorders. The three conditions evaluated in this study were COVID-19, viral Pneumonia, and normal lungs. Using X-ray pictures, this research developed a sparse categorical cross-entropy technique for recognizing all three categories. The proposed model had a training accuracy of 91% and a training loss of 0.63, as well as a validation accuracy of 81% and a validation loss of 0.7108.

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