Liver cancer detection is automated

CT scan (Computed Tomography) is basically an X-ray image, which can be used to provide clinicians with a detailed view of our internal organs, and can usually diagnose various forms of cancer. Previously, the use of CT to diagnose liver cancer was hindered to some extent by changes in the shape and structure of individual livers and the similarity of tissues in adjacent organs in CT images.

Amita Das of the Technical Education and Research Institute of the Department of Electronic and Communication Engineering at Siksha’O’Anusandhan University in Orissa, as well as Electrical Engineering at SCB Medical School and DY Patil Ramrao Adik Institute of Technology in Nerul, New Mumbai The department has developed a new texture analysis technology based on adaptive fuzzy clustering, which can be used to classify abdominal CT scans to diagnose liver cancer. This method is based on the extracted texture, morphology, and statistical features from the scan and using them as input, which can judge the neural network classifier to distinguish between benign and malignant liver tumors.

Today, they tested their method with a series of 45 images and studied sensitivity, specificity, and accuracy. The team was able to achieve nearly 99% accuracy in detecting tumors, and this result is already very good. The researchers’ next plan is to provide more data and training for the system, thereby further improving the reliability of the technology and developing an automatic diagnostic method that does not have the possibility of human error.

https://medicalxpress.com/news/2018-10-automated-liver-cancer.html

Susan Hau

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Susan Hau is a distinguished researcher in the field of cancer cell therapy, with a particular focus on T cell-based approaches and cancer vaccines. Her work spans several innovative treatment modalities, including CAR T-cell therapy, TIL (Tumor-Infiltrating Lymphocyte) therapy, and NK (Natural Killer) cell therapy.

Hau's expertise lies in cancer cell biology, where she has made significant contributions to understanding the complex interactions between immune cells and tumors.

Her research aims to enhance the efficacy of immunotherapies by manipulating the tumor microenvironment and exploring novel ways to activate and direct immune responses against cancer cells.

Throughout her career, Hau has collaborated with leading professors and researchers in the field of cancer treatment, both in the United States and China.

These international experiences have broadened her perspective and contributed to her innovative approach to cancer therapy development.

Hau's work is particularly focused on addressing the challenges of treating advanced and metastatic cancers. She has been involved in clinical trials evaluating the safety and efficacy of various immunotherapy approaches, including the promising Gamma Delta T cell therapy.

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