A brain tumor is a medical disorder faced by individuals of all demographics. Medically, it is described as the spread of non-essential cells close to or throughout the brain. Symptoms of this ailment include headaches, seizures, and sensory changes. This research explores two main categories of brain tumors: benign and malignant. Benign spreads steadily, and malignant expresses growth, making it dangerous. Early identification of brain tumors is a crucial factor for the survival of patients. This research provides a state-of-the-art approach to the early identification of tumors within the brain. We implemented the SegResNet architecture, a widely adopted architecture for three-dimensional segmentation, and trained it using the automatic multi-precision method. We incorporated the dice loss function and dice metric for evaluating the model. We got a dice score of 0.84. For the tumor core, we got a dice score of 0.84; for the whole tumor, 0.90; and for the enhanced tumor, we got a score of 0.79.

翻译：脑肿瘤是一种影响各年龄段人群的医学疾病。医学上将其描述为非必需细胞在脑部或脑部周围的扩散。该疾病的症状包括头痛、癫痫发作和感官变化。本研究主要探讨两类脑肿瘤：良性肿瘤与恶性肿瘤。良性肿瘤生长缓慢，而恶性肿瘤呈增殖性生长，具有危险性。脑肿瘤的早期识别是患者存活的关键因素。本研究提出了一种先进的脑部肿瘤早期识别方法。我们采用SegResNet架构——一种广泛用于三维分割的架构，通过自动混合精度方法进行训练。我们使用Dice损失函数和Dice指标评估模型，最终获得的Dice评分为0.84。其中肿瘤核心区域的Dice评分为0.84，整体肿瘤区域为0.90，增强肿瘤区域为0.79。