scholarly journals IMAGE SEGMENTATION OF CHEST X-RAYS FOR ABNORMALITY PATTERN RECOGNATION IN LUNGS USING FUZZY C-MEANS METHOD

2018 ◽  
Vol 2 (2) ◽  
pp. 13-23
Author(s):  
Matheus Alvian Wikanargo ◽  
Angelina Pramana Thenata
Keyword(s):  
Image Segmentation ◽  
The Body ◽  
Normal Lung ◽  
X Rays ◽  
Processing Stage ◽  
X Ray ◽  
Fuzzy C Means ◽  
Segmented Image ◽  
Chest X Ray ◽  
Normal Lungs

The lungs are one of the important and vital organs in the body that function as a respiratory system process. One way to detect lung disease is to do an X-rays test. Chest X-ray is a radiographic projection to detect abnormalities in lung organ by using x-ray radiation. In the process of diagnosing, doctors see the condition of the results of Chest X-rays in the form of a thorax image (chest) to know the patient has an abnormal or normal lung. However, doctors' diagnosis of chest X-rays results-based abnormalities is likely to differ depending on the doctor's abilities and experience. This problem is expected to be solved by segmenting the lung image to help make the diagnosis appropriately. The purpose of this study is to conduct an analysis that can differentiate abnormal and normal lungs. The process of recognition of these patterns consists of the pre-processing stage of image segmentation by using morphology and then proceed to grouping by using fuzzy c-means method to express the pattern of the already segmented image. This research produces normal and abnormal lung images that can be identified with an accuracy of 80%.

scholarly journals COVID-19 Pneumonia Detection Using Optimized Deep Learning Techniques

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1972
Author(s):  
Abul Bashar ◽  
Ghazanfar Latif ◽  
Ghassen Ben Brahim ◽  
Nazeeruddin Mohammad ◽  
Jaafar Alghazo
Keyword(s):  
Deep Learning ◽  
Transfer Learning ◽  
Data Augmentation ◽  
Learning Algorithm ◽  
The Body ◽  
X Rays ◽  
X Ray ◽  
Clinical Observations ◽  
Dataset Size ◽  
Chest X Ray

It became apparent that mankind has to learn to live with and adapt to COVID-19, especially because the developed vaccines thus far do not prevent the infection but rather just reduce the severity of the symptoms. The manual classification and diagnosis of COVID-19 pneumonia requires specialized personnel and is time consuming and very costly. On the other hand, automatic diagnosis would allow for real-time diagnosis without human intervention resulting in reduced costs. Therefore, the objective of this research is to propose a novel optimized Deep Learning (DL) approach for the automatic classification and diagnosis of COVID-19 pneumonia using X-ray images. For this purpose, a publicly available dataset of chest X-rays on Kaggle was used in this study. The dataset was developed over three stages in a quest to have a unified COVID-19 entities dataset available for researchers. The dataset consists of 21,165 anterior-to-posterior and posterior-to-anterior chest X-ray images classified as: Normal (48%), COVID-19 (17%), Lung Opacity (28%) and Viral Pneumonia (6%). Data Augmentation was also applied to increase the dataset size to enhance the reliability of results by preventing overfitting. An optimized DL approach is implemented in which chest X-ray images go through a three-stage process. Image Enhancement is performed in the first stage, followed by Data Augmentation stage and in the final stage the results are fed to the Transfer Learning algorithms (AlexNet, GoogleNet, VGG16, VGG19, and DenseNet) where the images are classified and diagnosed. Extensive experiments were performed under various scenarios, which led to achieving the highest classification accuracy of 95.63% through the application of VGG16 transfer learning algorithm on the augmented enhanced dataset with freeze weights. This accuracy was found to be better as compared to the results reported by other methods in the recent literature. Thus, the proposed approach proved superior in performance as compared with that of other similar approaches in the extant literature, and it made a valuable contribution to the body of knowledge. Although the results achieved so far are promising, further work is planned to correlate the results of the proposed approach with clinical observations to further enhance the efficiency and accuracy of COVID-19 diagnosis.

scholarly journals Karakteristik pasien benda asing trakeobronkial di bagian T.H.T.K.L Rumah Sakit Dr. Mohammad Hoesin Palembang

2018 ◽  
Vol 47 (2) ◽  
pp. 164
Author(s):  
Puspa Zuleika ◽  
Abla Ghanie
Keyword(s):  
Foreign Body ◽  
Foreign Bodies ◽  
Tracheobronchial Tree ◽  
Foreign Body Aspiration ◽  
The Body ◽  
X Rays ◽  
X Ray ◽  
Tracheobronchial Foreign Body ◽  
History Of ◽  
Chest X Ray

Latar belakang: Aspirasi benda asing ialah masuknya benda yang berasal dari luar atau dalam tubuh, ke saluran trakeobronkial. Aspirasi benda asing saluran trakeobronkial merupakan keadaan darurat yang memerlukan tindakan bronkoskopi segera untuk mencegah komplikasi yang lebih serius. Tujuan: Mengidentifikasi karakteristik klinis pasien aspirasi benda asing saluran trakeobronkial di bagian Telinga Hidung Tenggorok – Bedah Kepala Leher (T.H.T.K.L) Fakultas Kedokteran Universitas Sriwijaya/ Rumah Sakit Dr. Mohammad Hoesin Palembang. Metode: Penelitian ini merupakan penelitian observasional deskriptif. Sampel penelitian ini diambil dari data rekam medis pasien aspirasi benda asing pada saluran trakeobronkial di Rumah Sakit Dr. Mohammad Hoesin Palembang periode Januari 2012 - Desember 2016. Hasil: Didapatkan 20 pasien dengan riwayat teraspirasi benda asing di saluran trakeobronkial. Dijumpai 9 orang laki-laki dan 11 orang perempuan dengan perbandingan 1:1,2, di mana usia 0-15 tahun merupakan penderita terbanyak aspirasi benda asing ini. Benda asing yang paling banyak ditemukan adalah mainan dan benda plastik sebanyak 9 kasus, serta jarum pentul sebanyak 6 kasus. Sebanyak 19 pasien diketahui terdapat riwayat tersedak benda asing. Pemeriksaan foto toraks menunjukkan gambaran normal pada 12 pasien. Lokasi benda asing terbanyak ditemukan di trakea sebanyak 8 kasus. Kesimpulan: Aspirasi benda asing di saluran trakeobronkial sering terjadi pada anak-anak yang berusia kurang dari 15 tahun. Benda asing terbanyak adalah anorganik berupa mainan dan benda plastik. Pemeriksaan radiologi paru dalam 24 jam pertama setelah kejadian aspirasi pada umumnya menunjukkan gambaran normal. Lokasi benda asing di saluran trakeobronkial terbanyak pada penelitian ini adalah di trakea. Kata kunci: Aspirasi, bronkoskopi, foto toraks, benda asing, traktus trakeobronkial ABSTRACT Background: Foreign body aspiration is the entrance of foreign objects from outside or inside of the body into the tracheobronchial tract. Aspiration of foreign body in tracheobronchial tract is an emergency condition that needs immediate bronchoscopy procedure to prevent serious complications. Objectives: To identify clinical characteristics of foreign body aspiration patients in ENT Department Sriwijaya Medical Faculty / Dr. Mohammad Hoesin Hospital, Palembang. Method: This study was a descriptive observational study. The sample of this study was taken from the medical record of tracheobronchial foreign body aspiration patients at Dr. Mohammad Hoesin Hospital from January 2012 until December 2016. Result: There were twenty patients with the history of foreign body aspiration in tracheobronchial tract, consisted of 9 male and 11 female, with the ratio 1:1,2, in which 0–15 year-old children were the majority of the patients. The most common foreign bodies were toys and plastic objects in 9 cases and head veil pin in 6 cases. Nineteen cases of the patients had the history of choking as presenting symptom. Chest X-Ray showed normal imaging on twelve patients. The most common site in tracheobronchial tract where foreign bodies found was the trachea, in eight cases. Conclusions: Foreign body aspirations in tracheobronchial tract were most frequently happened in children less than 15 year-old. The most common foreign bodies were anorganic material, such as toys and plastic objects. Lung X-Rays on the first 24 hours commonly showed normal imaging. Foreign bodies in tracheobronchial tracts most frequently were found in the trachea. Keywords: Aspirations, bronchoscopy, chest X-Ray, foreign body, tracheobronchial tree

Detection of Pneumonia Using Chest X-Ray Images and Image Processing Algorithms - A Comparative Study

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Beena Ullala Mata B N ◽  
Rishika I. S ◽  
Nikita Jain ◽  
Kaliprasad C S ◽  
Niranjan K R
Keyword(s):  
Detection Algorithm ◽  
Contour Detection ◽  
Normal Lung ◽  
Lung Region ◽  
X Rays ◽  
X Ray ◽  
Otsu Thresholding ◽  
Chest X Ray ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Utilizing exclusively picture handling procedures, this examination proposes an original strategy for distinguishing the presence of pneumonia mists in chest X-rays (CXR). Collected the several analogue chest CXRs from patients with normal and Pneumonia-infected lungs. Indigenous algorithms have been developed for cropping and for extraction of the lung region from the images. To detect pneumonia clouds first conducted the preprocessing of the image then used the image segmentation techniques like Otsu thresholding K-means clustering and global thresholding and then contour detection algorithm was applied which helped to detect lung boundary, the area’s ratio is used to classify the normal lung from pneumonia affected lung.

X-ray micro tomography in the scanning electron microscope

1978 ◽  
Vol 36 (1) ◽  
pp. 106-107 ◽  
Author(s):  
W. Brünger
Keyword(s):  
Electron Beam ◽  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Target Surface ◽  
The Body ◽  
X Rays ◽  
Cross Sectional ◽  
X Ray ◽  
Micro Tomography ◽  
Scanning Electron

Reconstructive tomography is a new technique in diagnostic radiology for imaging cross-sectional planes of the human body /1/. A collimated beam of X-rays is scanned through a thin slice of the body and the transmitted intensity is recorded by a detector giving a linear shadow graph or projection (see fig. 1). Many of these projections at different angles are used to reconstruct the body-layer, usually with the aid of a computer. The picture element size of present tomographic scanners is approximately 1.1 mm2.Micro tomography can be realized using the very fine X-ray source generated by the focused electron beam of a scanning electron microscope (see fig. 2). The translation of the X-ray source is done by a line scan of the electron beam on a polished target surface /2/. Projections at different angles are produced by rotating the object.During the registration of a single scan the electron beam is deflected in one direction only, while both deflections are operating in the display tube.

Spontaneous Pneumomediastinum: Uncommon Cause of Air Leak in Late Preterm Neonate

2021 ◽  
Vol 35 (2) ◽  
pp. 93-94
Author(s):  
Jyotsna Bhushan ◽  
Shagufta Iqbal ◽  
Abhishek Chopra
Keyword(s):  
Respiratory Distress ◽  
Conservative Management ◽  
Preterm Neonate ◽  
Late Preterm ◽  
Intravenous Fluids ◽  
X Rays ◽  
Blood Gas ◽  
X Ray ◽  
Spontaneous Pneumomediastinum ◽  
Chest X Ray

A clinical case report of spontaneous pneumomediastinum in a late-preterm neonate, chest x-ray showing classical “spinnaker sail sign,” which was managed conservatively and had excellent prognosis on conservative management. Respiratory distress in a preterm neonate is a common clinical finding. Common causes include respiratory distress syndrome, transient tachypnea of the newborn, pneumonia, and pneumothorax. Pneumomediastinum is not very common cause of respiratory distress and more so spontaneous pneumomediastinum. We report here a preterm neonate with spontaneous pneumomediastinum who had excellent clinical recovery with conservative management. A male baby was delivered to G3P1A1 mother at 34 + 6 weeks through caesarean section done due to abruptio placenta. Apgar scores were 8 and 9. Maternal antenatal history was uneventful and there were no risk factors for early onset sepsis. Baby had respiratory distress soon after birth with Silverman score being 2/10. Baby was started on oxygen (O2) by nasal prongs through blender 0.5 l/min, FiO2 25%, and intravenous fluids. Blood gas done was normal. Possibility of transient tachypnea of newborn or mild hyaline membrane disease was kept. Respiratory distress increased at 20 h of life (Silverman score: 5), urgent chest x-ray done revealed “spinnaker sign” suggestive of pneumomediastinum, so baby was shifted to O2 by hood with FiO2 being 70%. Blood gas repeated was normal. Baby was managed conservatively on intravenous fluids and O2 by hood. Baby was gradually weaned off from O2 over next 5 days. As respiratory distress decreased, baby was started on orogastric feed, which baby tolerated well and then was switched to oral feeds. Serial x-rays showed resolution of pneumomediastinum. Baby was discharged on day 7 of life in stable condition on breast feeds and room air.

scholarly journals Accessory pathway analysis using a multimodal deep learning model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Makoto Nishimori ◽  
Kunihiko Kiuchi ◽  
Kunihiro Nishimura ◽  
Kengo Kusano ◽  
Akihiro Yoshida ◽  
...  
Keyword(s):  
Deep Learning ◽  
Electrophysiological Study ◽  
Accessory Pathway ◽  
Learning Model ◽  
X Rays ◽  
X Ray ◽  
Wpw Syndrome ◽  
Chest X Ray ◽  
Deep Learning Model ◽  
Ecg Data

AbstractCardiac accessory pathways (APs) in Wolff–Parkinson–White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using electrocardiography (ECG) and chest X-rays to identify the location of APs. We retrospectively used ECG and chest X-rays to analyse 206 patients with WPW syndrome. Each AP location was defined by an electrophysiological study and divided into four classifications. We developed a deep learning model to classify AP locations and compared the accuracy with that of conventional algorithms. Moreover, 1519 chest X-ray samples from other datasets were used for prior learning, and the combined chest X-ray image and ECG data were put into the previous model to evaluate whether the accuracy improved. The convolutional neural network (CNN) model using ECG data was significantly more accurate than the conventional tree algorithm. In the multimodal model, which implemented input from the combined ECG and chest X-ray data, the accuracy was significantly improved. Deep learning with a combination of ECG and chest X-ray data could effectively identify the AP location, which may be a novel deep learning model for a multimodal model.

scholarly journals 3D Imaging in Unilateral Primary Pulmonary Hypoplasia in an Adult: A Case Report

2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Aristida Georgescu ◽  
Crinu Nuta ◽  
Simona Bondari
Keyword(s):  
3D Imaging ◽  
Pulmonary Hypoplasia ◽  
Left Lung ◽  
Left Lobe ◽  
X Rays ◽  
X Ray ◽  
Female Smoker ◽  
Multidetector Computer Tomography ◽  
Biological Tests ◽  
Chest X Ray

Unilateral primary pulmonary hypoplasia is rare in adulthood (UPHA); it is characterized by a decreased number of bronchial segmentation and decreased/absent alveolar air space. Classical chest X-ray may be confusing, and the biological tests are unspecific. We present a case of UPHA in a 60-year-old female, smoker, with 3 term normal deliveries, who presented with late recurrent pneumonias and bronchiectasis-type symptomathology, arterial hypertension, and obesity. Chest X-rays revealed opacity in the left lower pulmonary zone, an apparent hypoaerated upper left lobe and left deviation of the mediastinum. Preoperatory multidetector computer tomography (MDCT) presented a small retrocardiac left lung with 5-6 bronchial segmentation range and cystic appearance. After pneumonectomy the gross specimen showed a small lung with multiple bronchiectasis and small cysts, lined by hyperplasic epithelium, surrounded by stromal fibrosclerosis. We concluded that this UPHA occurred in the 4–7 embryonic weeks, and the 3D MDCT reconstructions offered the best noninvasive diagnosis.

CHEST X RAY SCORE AND CLINICAL SEVERITY IN COVID-19 PATIENTS

2021 ◽  
pp. 31-32
Author(s):  
Sheeba Rana ◽  
Vicky Bakshi ◽  
Yavini Rawat ◽  
Zaid Bin Afroz
Keyword(s):  
Retrospective Study ◽  
Medical Records ◽  
Scoring Systems ◽  
Clinical Severity ◽  
X Rays ◽  
Antigen Test ◽  
X Ray ◽  
Classi Cation ◽  
Chest X Ray ◽  
Male Subjects

INTRODUCTION: Various chest X-ray scoring systems have been discovered and are employed to correlate with clinical severity, outcome and progression of diseases. With, the coronavirus outbreak, few chest radiograph classication were formulated, like the BSTI classication and the Brixia chest X-ray score. Brixia CXR scoring is used for assessing the clinical severity and outcome of COVID-19. This study aims to compare the Brixia CXR score with clinical severity of COVID-19 patients. MATERIAL& METHODS:This was a retrospective study in which medical records of patients aged 18 years or above, who tested for RTPCR or st st Rapid Antigen Test (RAT) for COVID positive from 1 February 2021 to 31 July 2021 (6 months) were taken. These subjects were stratied into mild, moderate and severe patients according to the ICMR guidelines. Chest X Rays were obtained and lesions were classied according to Brixia scoring system. RESULTS: Out of these 375 patients, 123 (32.8%) were female and 252 (67.2%) were male subjects. The average brixia score was 11.12. Average Brixia CXR score for mild, moderate and severe diseased subjects were 5.23, 11.20, and 14.43 respectively. DISCUSSION:The extent of chest x-ray involvement is proportional to the clinical severity of the patient. Although, a perplexing nding was that the average Brixia score of the female subjects were slightly higher than their male counterparts in the same clinical groups. CONCLUSION: Brixia CXR score correlates well with the clinical severity of the COVID-19.

Portable Ventilation/Perfusion Scanning is Useful for Evaluating Clinically Significant Pulmonary Embolism in the ICU Despite Abnormal Chest Radiography

2018 ◽  
Vol 35 (10) ◽  
pp. 1032-1038 ◽  
Author(s):  
Aaron S. Weinberg ◽  
William Chang ◽  
Grace Ih ◽  
Alan Waxman ◽  
Victor F. Tapson
Keyword(s):  
Pulmonary Embolism ◽  
Chest Radiograph ◽  
High Probability ◽  
Hemodynamic Instability ◽  
X Rays ◽  
X Ray ◽  
Abnormal Chest ◽  
Chest X Ray ◽  
Low Probability ◽  
Clinically Significant

Objective: Computed tomography angiography is limited in the intensive care unit (ICU) due to renal insufficiency, hemodynamic instability, and difficulty transporting unstable patients. A portable ventilation/perfusion (V/Q) scan can be used. However, it is commonly believed that an abnormal chest radiograph can result in a nondiagnostic scan. In this retrospective study, we demonstrate that portable V/Q scans can be helpful in ruling in or out clinically significant pulmonary embolism (PE) despite an abnormal chest x-ray in the ICU. Design: Two physicians conducted chart reviews and original V/Q reports. A staff radiologist, with 40 years of experience, rated chest x-ray abnormalities using predetermined criteria. Setting: The study was conducted in the ICU. Patients: The first 100 consecutive patients with suspected PE who underwent a portable V/Q scan. Interventions: Those with a portable V/Q scan. Results: A normal baseline chest radiograph was found in only 6% of patients. Fifty-three percent had moderate, 24% had severe, and 10% had very-severe radiographic abnormalities. Despite the abnormal x-rays, 88% of the V/Q scans were low probability for a PE despite an average abnormal radiograph rating of moderate. A high-probability V/Q for PE was diagnosed in 3% of the population despite chest x-ray ratings of moderate to severe. Six patients had their empiric anticoagulation discontinued after obtaining the results of the V/Q scan, and no anticoagulation was started for PE after a low-probability V/Q scan. Conclusion: Despite the large percentage of moderate-to-severe x-ray abnormalities, PE can still be diagnosed (high-probability scan) in the ICU with a portable V/Q scan. Although low-probability scans do not rule out acute PE, it appeared less likely that any patient with a low-probability V/Q scan had severe hypoxemia or hemodynamic instability due to a significant PE, which was useful to clinicians and allowed them to either stop or not start anticoagulation.

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