This research explores the use of features of cells in digital optical images of human thyroid tissue as an important base to diagnose the cancer. It presents some efficient features of cells nuclei for detection of thyroid malignancy such as (radius, smoothness, compactness, expected value and variance). The cytological characteristics are very important and usual method to separate abnormal and normal cases in all diseases. The algorithm of neural network used to detect thyroid cancer successfully with accuracy of 99%. Keywords: thyroid cancer, neural network, optical images, malignanc
Early diagnosis of thyroid cancer can reduce mortality, and can decrease the risk of recurrence, sid...
AbstractThis paper presents the classification of Papillary carcinoma and Medullary carcinoma cells ...
Computerized image analysis (IA) system has emerged in recent years as a very powerful tool for obje...
Objective. To investigate the application value of a deep convolutional neural network (CNN) model f...
Purpose: The purpose of the present study is to investigate the capability of the combination of Lea...
Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the...
Deep learning algorithms have achieved a tremendous triumph in task-specific feature classification....
Thyroid nodules are a common clinical problem. Ultrasonography (US) is the main tool used to sensiti...
Thyroid disease has now become the second largest disease in the endocrine field; SPECT imaging is p...
Computer-aided investigative processing has become an important part of medical practice. New growth...
Introduction: Fine-needle aspiration cytology (FNAC) for identification of papillary carcinoma thyro...
This paper describes automation methods for diagnostics of the thyroids gland carcinoma. It based on...
This research work presents an automated pattern recognition system to discriminate benign and malig...
Thyroid is one of the largest endocrine gland. It is a small butterfly shaped gland which is located...
Follicular lesions of the thyroid are traditionally difficult and tedious challenges in diagnostic s...
Early diagnosis of thyroid cancer can reduce mortality, and can decrease the risk of recurrence, sid...
AbstractThis paper presents the classification of Papillary carcinoma and Medullary carcinoma cells ...
Computerized image analysis (IA) system has emerged in recent years as a very powerful tool for obje...
Objective. To investigate the application value of a deep convolutional neural network (CNN) model f...
Purpose: The purpose of the present study is to investigate the capability of the combination of Lea...
Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the...
Deep learning algorithms have achieved a tremendous triumph in task-specific feature classification....
Thyroid nodules are a common clinical problem. Ultrasonography (US) is the main tool used to sensiti...
Thyroid disease has now become the second largest disease in the endocrine field; SPECT imaging is p...
Computer-aided investigative processing has become an important part of medical practice. New growth...
Introduction: Fine-needle aspiration cytology (FNAC) for identification of papillary carcinoma thyro...
This paper describes automation methods for diagnostics of the thyroids gland carcinoma. It based on...
This research work presents an automated pattern recognition system to discriminate benign and malig...
Thyroid is one of the largest endocrine gland. It is a small butterfly shaped gland which is located...
Follicular lesions of the thyroid are traditionally difficult and tedious challenges in diagnostic s...
Early diagnosis of thyroid cancer can reduce mortality, and can decrease the risk of recurrence, sid...
AbstractThis paper presents the classification of Papillary carcinoma and Medullary carcinoma cells ...
Computerized image analysis (IA) system has emerged in recent years as a very powerful tool for obje...