Artificial Intelligence for Digital and Computational Pathology
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence, including deep learning, have boosted the field of computational pathology. This field holds tremendous potential to automate clinical diagnosis, predict patient prognosis and response to therapy, and discover new morphological biomarkers from tissue images. Some of these artificial intelligence-based systems are now getting approved to assist clinical diagnosis; however, technical barriers remain for their widespread clinical adoption and integration as a research tool. This Review consolidates recent methodological advances in computational pathology for predicting clinical end points in whole-slide images and highlights how these developments enable the automation of clinical practice and the discovery of new biomarkers. We then provide future perspectives as the field expands into a broader range of clinical and research tasks with increasingly diverse modalities of clinical data.
Code (0)
등록된 구현이 없습니다.
Tasks
Prognosiswhole slide imagesSimilar Papers 제목 키워드 기반
Generative Adversarial Networks for Stain Normalisation in Histopathology
The rapid growth of digital pathology in recent years has provided an ideal opportunity for the development of artificial intelligence-based tools to improve the accuracy and efficiency of clinical diagnoses. One of the …
Survey of XAI in digital pathology
Artificial intelligence (AI) has shown great promise for diagnostic imaging assessments. However, the application of AI to support medical diagnostics in clinical routine comes with many challenges. The algorithms should…
DiagnosticExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)SurveySPLICE -- Streamlining Digital Pathology Image Processing
Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whole Slide Images (WSIs), there's a growing…
image-classificationImage Classificationwhole slide imagesTowards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology
Digital pathology is not only one of the most promising fields of diagnostic medicine, but at the same time a hot topic for fundamental research. Digital pathology is not just the transfer of histopathological slides int…
BIG-bench Machine LearningDiagnosticPrognosisRCdpia: A Renal Carcinoma Digital Pathology Image Annotation dataset based on pathologists
The annotation of digital pathological slide data for renal cell carcinoma is of paramount importance for correct diagnosis of artificial intelligence models due to the heterogeneous nature of the tumor. This process not…