眼动追踪已经使用了几十年来试图理解个体的认知过程。从内存访问到解决问题再到决策,这种洞察力有可能改善工作流程和教育学生成为相关领域的专家。直到最近,显微镜在病理学中的传统使用使得眼睛追踪异常困难。然而,从传统显微镜到数字全幻灯片图像的病理学数字革命允许进行新的研究和信息学习关于病理学家的视觉搜索模式和学习经验。这有望使病理学教育更加高效和引人入胜,最终创造出更强大、更熟练的病理学家。这篇关于病理学眼动追踪的评论的目的是表征和比较病理学家的视觉搜索模式。使用“病理学”和“眼动追踪”同义词搜索PubMed和WebofScience数据库。截至2023年,共发表了22篇相关全文文章,并将其纳入本综述。进行主题分析,将每项研究组织成10个主题中的一个或多个,以表征病理学家的视觉搜索模式:(1)经验的影响,(2)固定,(3)缩放,(4)平移,(5)扫视,(6)瞳孔直径,(7)口译时间,(8)战略,(9)机器学习,(10)教育。专家病理学家被发现有更高的诊断准确性,更少的关注,与经验较少的病理学家相比,解释时间更短。Further,关于病理学中的眼动追踪的文献表明,有几种用于数字病理图像诊断解释的视觉策略,但没有证据表明有优越的策略.还探索了眼动追踪在病理学中的教育意义,但是教新手如何以专家身份进行搜索的效果尚不清楚。在这篇文章中,简要讨论了眼动追踪在病理学中的主要挑战和前景,以及它们对该领域的影响。
Eye tracking has been used for decades in attempt to understand the cognitive processes of individuals. From memory access to problem-solving to decision-making, such insight has the potential to improve workflows and the education of students to become experts in relevant fields. Until recently, the traditional use of microscopes in pathology made eye tracking exceptionally difficult. However, the digital revolution of pathology from conventional microscopes to digital whole slide images allows for new research to be conducted and information to be learned with regards to pathologist visual search patterns and learning experiences. This has the promise to make pathology education more efficient and engaging, ultimately creating stronger and more proficient generations of pathologists to come. The goal of this review on eye tracking in pathology is to characterize and compare the visual search patterns of pathologists. The PubMed and Web of Science databases were searched using \'pathology\' AND \'eye tracking\' synonyms. A total of 22 relevant full-text articles published up to and including 2023 were identified and included in this review. Thematic analysis was conducted to organize each study into one or more of the 10 themes identified to characterize the visual search patterns of pathologists: (1) effect of experience, (2) fixations, (3) zooming, (4) panning, (5) saccades, (6) pupil diameter, (7) interpretation time, (8) strategies, (9) machine learning, and (10) education. Expert pathologists were found to have higher diagnostic accuracy, fewer fixations, and shorter interpretation times than pathologists with less experience. Further, literature on eye tracking in pathology indicates that there are several visual strategies for diagnostic interpretation of digital pathology images, but no evidence of a superior strategy exists. The educational implications of eye tracking in pathology have also been explored but the effect of teaching novices how to search as an expert remains unclear. In this article, the main challenges and prospects of eye tracking in pathology are briefly discussed along with their implications to the field.