Detection of Architectural Distorted Region in Mammogram Images Using Hybrid Classification Approaches

The architectural distorted regions in mammogram images are detected and segmented using computer aided hybrid classification approach in this paper. The main importance of this research work is to provide a computer aided methodology for screening the distorted regions in mammogram images. In present approach, the classification accuracy of the conventional methods is not suitable for further diagnosis process such as malignant and benign. Hence, the main objective of this paper is to develop an efficient architectural region detection method using soft computing method with high classification accuracy for further diagnosis purpose. This proposed method has two stages of the proposed flow as architectural distorted detected mammogram image and segmentation of architectural distorted regions in mammogram images. The first stage of this proposed method uses Random Forest (RF) classification method which classifies the source mammogram image into either normal or abnormal. In second stage of the proposed method, the abnormal image is further classified into either Benign or Malignant using Adaptive Neuro Fuzzy Inference System (ANFIS) classification approach. The proposed methodology for architectural distorted region detection is tested on the publicly available mammogram datasets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) respectively. In this paper, the mammogram images from MIAS dataset are grouped into normal case (156 images), benign case (122 images) and malignant case (98 images). The mammogram images from DDSM dataset are grouped into normal case (144 images), benign case (112 images) and malignant case (145 images). The overall average detection rate of the proposed system on the mammogram images in MIAS dataset is about 98.7%. The overall average detection rate of the proposed system on the mammogram images in DDSM dataset is about 98.3%. The extensive simulations are carried out on the mammogram images which are obtained from these dataset and the results are compared with stated of art methods.

Benign Calcified Thyroglossal Duct Cyst, – Defying The Hallmark of Papillary Carcinoma, 4th Case Reported In Literature

Thyroglossal duct cyst is the most common upper neck midline lesion in children. Approximately 1% of thyroglossal duct cyst undergoes malignant transformation. Calcification which is a marker of malignancy almost always points out to papillary thyroid carcinoma. Benign case of calcified thyroglossal cyst maybe undiagnosed or under reported. We report a case of a 5 year old girl with a benign calcified thyroglossal duct cyst, a fourth case in world literature. Here the differences between a benign and malignant thyroglossal duct cyst are discussed.

Case report. Longitudinal Echo Monitoring in Fetus with Phenotypical Marfan Syndrome, Helpfull for Perinatal Management - Case Presentation and Literature Review

It was the second pregnancy of an otherwise healthy married couple. The fetus (male) had detailed echocardiography monitoring in the second half of the pregnancy due to progression of cardiomegaly, and echocardiographic features of congestive heart failure. Marfan syndrome was suspected based on cardiac anomalies. For the first time, the rupture of aneurysm of aortic sinus Valsalva was documented. Despite transplacental treatment with digoxin there was fetal demise at the 34th week of gestation and postmortem newborn phenotype confirmed prenatal diagnosis. Marfan Syndrome is a rare genetic anomaly which can be diagnosed prenatally by detailed echocardiography, usually with bad prognosis (just opposite to “benign” case diagnosed later on in life span). The most common prenatal cardiac manifestations are cardiomegaly with signs of cardiac insufficiency. We present the case with new echocardiographic features.

Oxidation of Inorganic Contaminants by Ferrates (VI) - A Review

This review makes a critical assessment of the oxidation a series of inorganic compounds by ferrates eFeVIO42_; Inorganic contaminants are found in water, wastewaters, and industrial effluents and their oxidation using iron based oxidants is of great interest because such oxidants possess multi-functional properties and are environmentally benign. Case studies are presented which demonstrate that inorganic contaminants can be degraded in seconds to minutes by ferrate (VI) with the formation of non-toxic products.