Mass lesions are one of the breast cancer tumors. Mammogram images first screening tool to detect tumors in women breast, but due radiologist fatigue, number false positive (FP) and negative (FN) rates increased. The main objective this paper is develop an intelligent computer aided diagnosis (CAD) system that can accurately mass digitized mammogram images. proposed method has three stages. sta...

The development of a new soft tissue lesion in an otherwise healthy child, adolescent, or young adult can present many challenges for pediatric or medical oncology teams. Although uncommon, the diagnosis of a soft tissue malignancy should always be considered in the differential diagnosis of persistent pain, even if no mass is palpable. The definitive diagnosis and treatment of a soft tissue ma...

abstract background: a tumefactive lesion of central nervous system (cns) is defined as a mass-like lesion with a size greater than 2 cm in brain (magnetic resonance imaging) mri. neuroimaging may help to distinguish the nature of a tumefactive lesion and therefore can prevent an unnecessary brain biopsy. method: in this paper, we have emphasized on determining the nature of a cns tumefactive l...

The shapes of malignant breast tumors are more complex than the benign lesions due to their nature of infiltration into surrounding tissues. We investigated the efficacy of shape features and presented a method using polygon shape complexity to improve the discrimination of benign and malignant breast lesions on ultrasound. First, 63 lesions (32 benign and 31 malignant) were segmented by K-way ...

PATIENT Female, 60 FINAL DIAGNOSIS: Inflammatory pseudotumor of the lung Symptoms: Cough dry • fever MEDICATION - Clinical Procedure: - Specialty: - OBJECTIVE Rare disease. BACKGROUND Inflammatory pseudotumor of the lung involves a benign, non-neoplastic lung lesion of unknown etiology. CASE REPORT We present a case of a 60-year-old female smoker who had been under intermittent immunosu...

In recent years, convolutional neural networks (CNNs), due to their powerful end-to-end feature learning capabilities, have been widely used in medical aided diagnosis. general, a dermatologist's diagnostic process first identifies the type of skin lesions, and then obtains diagnosis diseases according recognition lesions. However, most existing methods only focus on designing diverse directly ...

Abstract Cancer is the second leading cause of death worldwide. Brain tumors count for one out every four cancer deaths. Providing an accurate and timely diagnosis can result in treatments. In recent years, rapid development image classification has facilitated computer-aided diagnosis. The convolutional neural network (CNN) most widely used models classifying images. However, its effectiveness...

Dermatologists have stated their preference for computer aided diagnosis (CAD) systems that provide medical justifications for the estimated diagnosis of a skin lesion. Such systems are considered to be clinically oriented in the sense that they try to detect clinical criteria and then perform a diagnosis based on that information. Unfortunately, the development of clinically inspired systems i...

Advances in medical digital imaging have greatly benefited patient care. Computer-aided diagnosis is increasingly being used to facilitate semior fullyautomatic medical image analysis and image retrieval. While different tasks involve different methodologies in this domain, these tasks normally require image feature extraction as an essential component in the algorithmic framework. In this Chap...