Image enhancement technology is widely used to improve images and help radiologists make more accurate cancer diagnoses. In this research work presents an integrating approach for contrast enhancement followed by the segmentation of breast cancer from the mammogram images. The proposed method has been effectively utilized the three different algorithms such as differential Evolution (DE) Algorithm, Kernel Based Fuzzy C Means (KFCM) Clustering and Cuckoo Search Optimization (CSO) algorithm. Here an integrating approach introduced, called Optimized Kernel Fuzzy Adaptive Gamma Correction with Weighed Distribution (OKF-AGCWD) based Level Set Method. The performance of proposed method is enhanced over existing level set methods such as image and vision computing (IVC)-2010, IVC-2013, and Expert Systems with Applications (ESA) 2021. The performance metric parameters like F1_score, Sensitivity, Specificity and accuracy are considered to assess the quality of different methods. The simulation was performed on 16 distinct images from the RIDER mammography database. The experimental results were compared with existing level set approaches such as image and vision computing (IVC)2010, IVC2013 and expert systems and applications (ESA)2021 with respect to OKF-AGCWD. The proposed OKF-AGCWD with contextual level set method (CLSM) minimizes boundary leakage problem of mammogram segmented image and improves segmentation accuracy. 

The WSN (Wireless Sensor Network) is the most appearing expertise that has potential applications broad ranges that include environment examining, smart spaces, medical systems, and robotic study. The efficient energy is a consideration of vital design for WSN. In WSNs, the collision is occurred due to data transmission from the sensor nodes and the traffic at SINK node is high due to the transmission of excess data by the sensor nodes. An important division of the consumption of resources in a WSN is managed by the mechanism of MAC (Medium Access Control). An existing MAC protocols initiated for the utilization of WSNs single channel for the transmission of data. This is basically because of the reality that efficient energy is measured to be the issue of essentiality in WSNs. A new multi-channel MAC procedure MPCB-HM is proposed which utilizes CSMA/CA (Carrier Sense Multiple Access/ Collision Avoidance), to exchange the data, the activity of TDMA (Time Division Multiple Access) sequencing nodes and also FDMA (Frequency Division Multiple Access) to allow collision-free exchange simultaneously.  The nodes have multiple communication channels, so that the high data traffic can be shared in multiple channels. This reduces the overhead in the nodes and the Energy consumption is minimized by this method and collision free transmission is achieved. With the help of intra-cluster communication and inter-cluster communication, the MAC mode control is responsible for shifting of mode from TDMA to CSMA and vice versa. The Cluster-based topology is implemented which helps in improving the scalability and energy efficiency. By utilizing the simulator of NS2, the process is estimated and the outcomes have shown that the procedure of MAC is improved by overall network presentation compared to the other protocols.