Browsing by Subject "Magnetic resonance imaging."

Now showing items 1-4 of 4

    • Brain tumor sectionalization through semantic segmentation approach 

      Dibbya, Tirthankar Saha; Khan, Md. Sayem; Tarannum, Tasfia; Mahin, Rahmat Ullah (Brac University, 2024-10)
      Accurate brain tumor detection and segmentation from magnetic resonance imaging (MRI) scans are vital for effective diagnosis, treatment planning, and patient monitoring. However, manual segmentation is time-consuming ...

    • An efficient deep learning-based approach for Glioblastoma detection from MRI images 

      Saihan, Ismail Hossain; Tamanna, Umme Mahbuba; Tahmid, Ms Rodsy; Fardin, Md. Rahadul Islam; Romit, Fahim Ahamed (BRAC University, 2024-10)
      In essence, an abnormal increase of brain cells is referred to as a brain tumor. Tumors come in two varieties: benign (non-cancerous) and malignant (cancerous). Cancerous tumors can originate in the brain itself (Primary) ...

    • An efficient ML approach to detect brain tumor using MRI images 

      Muktadir, MD. Arafat; Ullah, A.S.M Rahmat; Hossain, Emdad; Islam, MD. Jubayer; Munny, Tanjila Akter (Brac University, 2023-05)
      Brain tumors have become the most leading causes of death worldwide. Brain tumors can be fatal, have a severe impact on quality of life, and completely alter a patient’s and their loved ones’ lives. Early diagnosis of ...

    • In-depth analysis of deep learning architectures for brain tumor classification in MRI scans 

      Haque, Hossain MD. Hasibul; Apon, MD. Sayeed Arefin; Chowdhury, Dhrubo Rashid; Imtiaz, Shahriar Islam; Mahi, Nishat Tasnim (Brac University, 2024)
      One of the deadliest and most difficult tumors to cure is a brain tumor. Patients diagnosed with brain tumors tend to have a comparatively shorter lifespan. This tumor can affect any individual of any age. To mitigate ...