Computer-Aided Detection (CAD) and Assessment of Malignant Lesions in the Liver and Lung using a Novel PET/CT Software Tool: Initial Results

Author(s):  
S. Hahn ◽  
T. Heusner ◽  
X. Zhou ◽  
Y. Zhan ◽  
Z. Peng ◽  
...  
2002 ◽  
Vol 12 (12) ◽  
pp. 3015-3017 ◽  
Author(s):  
F. Baum ◽  
U. Fischer ◽  
S. Obenauer ◽  
E. Grabbe

2016 ◽  
Vol 2 (1) ◽  
pp. 12-16
Author(s):  
Lina Choridah ◽  
Nurhuda Hendra Setyawan ◽  
Faisal Najamuddin ◽  
Hanung Adi Nugroho

Objectives: Mammography has an important role in the diagnosis of breast cancer. computer-aided detection (CADe) or computeraided diagnosis (CADx) systems have been developed to improve the capability of radiologists to interpret medical images and to di?erentiate benign and malignant lesions. We studied the capability of ICA as a technique used in CAD systems.Methods: An observational study involving 20 participants (5 radiologists and 15 last year radiology residents) has been initiated. First, they performed assessment of the 60 digitized flm mammograms consisting of 27 normal and 33 abnormal mammograms. Subsequently, from the 33 mammograms with pathological massed, they were asked to di?erentiate benign and malignant lesions (15 and 18 mammograms, respectively).Results: The sensitivity to detect the abnormal lesions in the mammograms was 70% and the specifcity was 72.78%, increased to 74% and 88%, respectively when using ICA. The sensitivity and specifcity to di?erentiate between benign and malignant lesions turned from 40.8 % and 80.3% to 62.5% and 68% after using ICA. The missed diagnostic rate in mammography increased especially in dense breast.Conclusion: ICA improves the radiologists detection of abnormal lesions in mammograms so that it can properly be used as CADe. However, ICA might not be used as a CADx.


2013 ◽  
Vol 37 (2) ◽  
pp. 283-288 ◽  
Author(s):  
Marc Lobbes ◽  
Marjolein Smidt ◽  
Kristien Keymeulen ◽  
Rossano Girometti ◽  
Chiara Zuiani ◽  
...  

2007 ◽  
Vol 46 (01) ◽  
pp. 43-48 ◽  
Author(s):  
G. Wolz ◽  
A. Nömayr ◽  
T. Hothorn ◽  
J. Hornegger ◽  
W. Römer ◽  
...  

Summary Aim: Comparison of anatomical accuracy of softwarebased interactive (IRR) and automated rigid registration (ARR) of separately acquired CT and FDG-PET data sets. Patients, methods: Independently acquired PET and helical CT data from 22 tumour patients were registered manually using the Syngo advanced Fusion VC20H tool. IRR was performed separately for the thorax and the abdomen using physiological FDG uptake in several organs as a reference. In addition, ARR was performed with the commercially available software tool Mirada 7D on all of the patients. For both methods, the distances between the representation of 53 malignant lesions on PET and CT were measured in X-, Y-, and Z-direction with reference to a common coordinate system (X-, Y-, Z-distances). Results: The percentage of lesions misregistered by less than 1.5 cm was in X-direction 91% for IRR and 89% for ARR; in Y-direction 85% and 68%; in Z-direction 72% and 51%, respectively. The average X-, Y- and Z-distances for IRR ranged from 0.58 ± 0.55 cm (X-direction) to 1.17 ± 1.66 cm (Z-direction). For ARR, the average X-, Y- and Z-distances varied between 0.66 ± 0.61 cm (X-direction) and 1.81 ± 1.37 cm (Z-direction). Mixed effects analysis of the absolute X-, Y- and Z-distances revealed a significantly better alignment for IRR compared to ARR in Z-direction (p <0.01). Lesion size and localization either in thorax or abdomen had no significant influence on the accuracy of registration. Conclusion: For the majority of malignant lesions, manual image registration with the possibility to separately align different body segments was more accurate than the automated approach. Current software for ARR does not reach the anatomical accuracy reported for PET/ CT hybrid scanners.


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