Diagnosis of the Medical Images Using a Three-Dimensional MRI and CT Reconstruction Algorithm: A Study Protocol for a Randomized Controlled Trial

Abstract

Prognostic signs in the cervix, tumour size, parametric invasion, pelvic lateral wall, and lymph node invasion can all be effectively assessed by MRI and CT. CT has a high-density resolution and can clearly show organs and soft tissue structures with small density differences. Despite the importance of MRI and CT in cervical cancer and thyroid cancer assessment, radiologists continue to confront hurdles due to the technical and interpretive pitfalls of MRI. Furthermore, precise thyroid cancer diagnosis and staging (using MRI and CT imaging) allows for the development of a successful treatment plan. The dosimetry of radioactive iodine therapy and the evaluation of the therapeutic impact both require precise thyroid volume measurements. Thyroid size has become a criterion in the selection of patients for minimally invasive surgery in surgical intervention. Our research is unique in two ways: first, we validate the computer assisted diagnostic (CAD) method in a clinical study; and second, we use various network topologies specified above, that have produced impressive outcomes in the activities of image model recognition, and we specialise this network mix by requalifying the last layers with field specific images-MRI and CT scan.