[EN] This article presents a pattern-recognition approach to the soft tissue tumors (STT) benign/malignant character diagnosis using magnetic resonance (MR) imaging applied to a large multicenter database. Objective: To develop and test an automatic classifier of STT into benign or malignant by using classical MR imaging findings and epidemiological information. Materials and methods: A database of 430 patients (62% benign and 38% malignant) from several European multicenter registers. There were 61 different histologies (36 with benign and 25 with malignant nature). Three pattern-recognition methods (artificial neural networks, support vector machine, k-nearest neighbor) were applied to learn the discrimination between benignity and malign...
Correct diagnosis of the liver tumor phenotype is crucial for treatment planning, especially the dis...
Brain Tumor originates from abnormal cells, which is developed uncontrollably. Magnetic resonance im...
Simple Summary In soft-tissue sarcoma (STS) patients, the decision for the optimal treatment modalit...
There is a variable degree of accuracy in discriminating benign from malignant soft tissue masses ba...
BackgroundThere is a variable degree of accuracy in discriminating benign from malignant soft tissue...
A blinded, retrospective review of 83 soft-tissue masses (49 benign and 34 malignant) was performed ...
The brain is one of the most complex organ in the human body that works with billions of cells. A ce...
The use of digital image processing has become very demanding in various areas including medical app...
Aims: Various features have been described in the literature to differentiate benign from malignant...
An intracranial mass of abnormal cells in the brain that have grown out of control is referred to as...
Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backin...
Contains fulltext : 60658.pdf (publisher's version ) (Open Access)The purpose of t...
The purpose of this article is to investigate techniques for classifying tumor grade from magnetic r...
This paper presents some case study frameworks to limelight SVM classifiers as most efficient one co...
Brain tumor is one of the commonest tumors. For the diagnosis of this disease, automated detection a...
Correct diagnosis of the liver tumor phenotype is crucial for treatment planning, especially the dis...
Brain Tumor originates from abnormal cells, which is developed uncontrollably. Magnetic resonance im...
Simple Summary In soft-tissue sarcoma (STS) patients, the decision for the optimal treatment modalit...
There is a variable degree of accuracy in discriminating benign from malignant soft tissue masses ba...
BackgroundThere is a variable degree of accuracy in discriminating benign from malignant soft tissue...
A blinded, retrospective review of 83 soft-tissue masses (49 benign and 34 malignant) was performed ...
The brain is one of the most complex organ in the human body that works with billions of cells. A ce...
The use of digital image processing has become very demanding in various areas including medical app...
Aims: Various features have been described in the literature to differentiate benign from malignant...
An intracranial mass of abnormal cells in the brain that have grown out of control is referred to as...
Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backin...
Contains fulltext : 60658.pdf (publisher's version ) (Open Access)The purpose of t...
The purpose of this article is to investigate techniques for classifying tumor grade from magnetic r...
This paper presents some case study frameworks to limelight SVM classifiers as most efficient one co...
Brain tumor is one of the commonest tumors. For the diagnosis of this disease, automated detection a...
Correct diagnosis of the liver tumor phenotype is crucial for treatment planning, especially the dis...
Brain Tumor originates from abnormal cells, which is developed uncontrollably. Magnetic resonance im...
Simple Summary In soft-tissue sarcoma (STS) patients, the decision for the optimal treatment modalit...