Colorectal cancer (CRC) is the third leading cause of death globally. Early detection and removal precancerous polyps can significantly reduce chance CRC patient death. Currently, polyp rate mainly depends on skill expertise gastroenterologists. Over time, unidentified develop into cancer. Machine learning has recently emerged as a powerful method in assisting clinical diagnosis. Several classification models have been proposed to identify polyps, but their performance not comparable an...

One of the fundamental and crucial tasks for automated diagnosis colorectal cancer is segmentation acute gastrointestinal lesions, most commonly polyps. Therefore, in this work, we present a novel lightweight encoder-decoder mode architecture with attention mechanism to address challenging task.The proposed Li-SegPNet harnesses cross-dimensional interaction feature maps encoder block modified triplet attention. We have used atrous spatial pyramid pooling handle problem segmenting objects at...

In this paper, we address a current problem in medical image processing, the detection of colorectal cancer from colonoscopy videos. According to worldwide statistics, is one most common cancers. The process screening and removal pre-cancerous cells large intestine crucial task date. traditional manual dependent on expertise practitioner. two-stage classification proposed detect cancer. first stage, frames video are extracted rated as significant if it contains polyp, these results then...

Melanoma is a type of skin cancer that starts in the cells (melanocytes) govern color your skin. most lethal one among all other diseases and only reason for 77% deaths due to cancer. The best way reduce these detect at its early stages so it can be treated cured with minor treatment or surgeries. To speed up improve process detection, we propose an automatic classification method melanoma using advanced deep neural network. Deep learning models require large dataset work efficiently, but...

Several brain diseases are becoming a threat to the livelihood of people. One such problem is presence tumour. A tumour can be benign or malignant. It dangerous if it malignant secondary (metastasis). Therefore, there need detect tumours at earliest stage as possible. Using an automated method for detection solution medical expertise biopsy excluded early could Classification helps in prediction type image and In this paper, three stages involved. first stage, classification MR images into...

Colorectal Cancer has become a major cause of death in recent times. To improve the chances survival, detecting early signs and identifying polyps routine examination is necessary. In this pursuit, an automatic computer-aided diagnosis (CAD) system to detect disease onset crucial. Deep Learning at base advances CAD systems, its successes encourage it be used colorectal cancer analysis. Efficient segmentation from colonoscopy images can aid radiologists immensely task identification...

Abstract The traditional process of disease diagnosis from medical images follows a manual process, which is tedious and arduous. A computer‐aided (CADs) system can work as an assistive tool to improve the process. In this pursuit, article introduces unique architecture LPNet for classifying colon polyps colonoscopy video frames. Colon are abnormal growth cells in wall. Over time, untreated may cause colorectal cancer. Different convolutional neural networks (CNNs) based systems have been...

Medical sciences have a major role in every person's life. From children to old age people, all need treatment for various diseases. Though it has tremendous impact, still lacks cure many diseases, one of which is brain tumor. Brain tumor can be dangerous if malignant or secondary and needed proper evaluation their treatment. Clinically, the efficiency accuracy are important such For this purpose, automated detection use, where we detect classify without human intervention. classification an...

Background: Breast and cervical cancers are leading causes of deaths in India among female population. To reduce the mortality rate, awareness is major concern current time. Objective: study breast common women based on different factors such as age, residence, occupation. Materials Methods: A cross-sectional was performed 1000 who can efficiently represent age groups, occupation, place residence. Study population were subdivided into two equal groups where one group participated...

Colonic polyp detection during colonoscopy is an essential and crucial task towards the improvement of automatic colon cancer. Advancement technology in field medical image analysis helps to identify anomalies its early phase therapy planning process. The work presented here a methodology focused on deep learning techniques that give edge identification existence polyps. This proposed approach could serve as assistive tool process colonoscopy.

<h3>Objectives</h3> To find out percentage of female doctors who have undergone screening for cervical cancer. asses knowledge and attitude cancer in doctors. reasons non-screening those never had any screening. <h3>Methods</h3> This was a questionnaire based study done Jodhpur. After informing the purpose study, printed given asked to fill data. Identity person kept confidential Questions comprised whether they themselves got screened, about not getting screened <h3>Results</h3> 440 forms...

Several brain diseases are becoming a threat to the livelihood of people. One such problem is presence tumour. A tumour can be benign or malignant. It dangerous if it malignant secondary (metastasis). Therefore, there need detect tumours at earliest stage as possible. Using an automated method for detection solution medical expertise biopsy excluded early could Classification helps in prediction type image and In this paper, three stages involved. first stage, classification MR images into...