Computer-assisted discrimination among malignant lymphomas and leukemia using immunophenotyping, intelligent image repositories, and telemicroscopy

被引:49
作者
Foran, DJ [1 ]
Comaniciu, D
Meer, P
Goodell, LA
机构
[1] Univ Med & Dent New Jersey, Robert Wood Johnson Med Sch, Ctr Biomed Imaging & Informat, Piscataway, NJ 08854 USA
[2] Siemens Corp Res, Dept Imaging & Visualizat, Princeton, NJ 08540 USA
[3] Rutgers State Univ, Dept Comp & Elect Engn, Piscataway, NJ 08854 USA
[4] Univ Med & Dent New Jersey, Robert Wood Johnson Med Sch, Dept Pathol & Lab Med, Piscataway, NJ 08854 USA
来源
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 2000年 / 4卷 / 04期
基金
美国国家科学基金会;
关键词
D O I
10.1109/4233.897058
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The process of discriminating among pathologies involving peripheral blood, bone marrow, and lymph node has traditionally begun with subjective morphological assessment of cellular materials viewed using light microscopy. The subtle visible differences exhibited by some malignant lymphomas and leukemia, however, give rise to a significant number of false negatives during microscopic evaluation by medical technologists. We have developed a distributed, clinical decision support prototype for distinguishing among hematologic malignancies, The system consists of two major components, a distributed telemicroscopy system and an intelligent image repository. The hybrid system enables individuals located at disparate clinical and research sites to engage in interactive consultation and to obtain computer-assisted decision support. Software, written in JAVA, allows primary users to control the specimen stage, objective lens, light levels, and focus of a robotic microscope remotely while a digital representation of the specimen is continuously broadcast to all session participants, Primary user status can be passed as a token, The system features shared graphical pointers, test messaging capability, and automated database management. Search engines for the database allow one to automatically identify and retrieve images, diagnoses, and correlated clinical data of cases from a "gold standard" database which exhibit spectral and spatial profiles which are most similar to a given query image. The system suggests the most likely diagnosis based on majority logic of the retrieved cases. The system was used to discriminate among three lymphoproliferative disorders and healthy cells. The system provided the correct classification in more than 83% of the cases studied. System performance was evaluated using rigorous statistical assessment and by comparison with human observers.
引用
收藏
页码:265 / 273
页数:9
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