AIMC Topic: Tomography, X-Ray Computed

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Three-dimensional image volumes from two-dimensional digitally reconstructed radiographs: A deep learning approach in lower limb CT scans.

Medical physics
PURPOSE: Three-dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years now. The different image modalities usually rely on several consecutive two-dimensional (2D) acquisit...

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

Medical image analysis
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We de...

Semi-supervised learning for an improved diagnosis of COVID-19 in CT images.

PloS one
Coronavirus disease 2019 (COVID-19) has been spread out all over the world. Although a real-time reverse-transcription polymerase chain reaction (RT-PCR) test has been used as a primary diagnostic tool for COVID-19, the utility of CT based diagnostic...

A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.

International journal of computer assisted radiology and surgery
PURPOSE: In this study, we try to consider the most common type of total anomalous pulmonary venous connection and established a machine learning-based prediction model for postoperative pulmonary venous obstruction by using clinical data and CT imag...

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT.

Radiology
Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance of a CT radiomics-based machine learning model for differentiating bone islands and osteoblastic bo...

Machine learning is the key to diagnose COVID-19: a proof-of-concept study.

Scientific reports
The reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coronavirus disease 2019 (COVID-19) diagnosis. As any test, RT-PCR provides false negative results that can be rectified by clinicians by confronting clin...

Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.

International journal of computer assisted radiology and surgery
PURPOSE: Nasopharyngeal carcinoma (NPC) is a category of tumors with high incidence in head-and-neck (H&N) body region, and the diagnosis and treatment planning are usually conducted by radiologists manually, which is tedious, time-consuming and unre...

Detecting the Early Infarct Core on Non-Contrast CT Images with a Deep Learning Residual Network.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: To explore a new approach mainly based on deep learning residual network (ResNet) to detect infarct cores on non-contrast CT images and improve the accuracy of acute ischemic stroke diagnosis.

Management of Significant Airway Bleeding during Robotic Assisted Bronchoscopy: A Tailored Approach.

Respiration; international review of thoracic diseases
Robotic assisted bronchoscopy represents a major turning point in bronchoscopic history. The management strategies to address significant airway bleeding in this "robotic era" are not well documented, and further guidance is required. We present a ca...

Machine Learning in Body Composition Analysis.

European urology focus
Body composition analysis (BCA) generates objective anthropometric data that can inform prognostication and treatment decisions across a wide variety of urologic conditions. A patient's body composition, specifically muscle and adipose tissue mass, m...