Maurice Samulski

Maurice Samulski
Radboud University | RU · Department of Radiology

PhD

About

29
Publications
4,956
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408
Citations

Publications

Publications (29)
Article
Purpose: To compare effectiveness of an interactive computer-aided detection (CAD) system, in which CAD marks and their associated suspiciousness scores remain hidden unless their location is queried by the reader, with the effect of traditional CAD prompts used in current clinical practice for the detection of malignant masses on full-field digit...
Article
Objectives We developed a computer-aided detection (CAD) system aimed at decision support for detection of malignant masses and architectural distortions in mammograms. The effect of this system on radiologists' performance depends strongly on its standalone performance. The purpose of this study was to compare the standalone performance of this C...
Thesis
Full-text available
For many years, it has been recognized that even the best radiologists make errors when reading medical exams including perception failures and interpretation failures. To reduce these problems, computer aided detection and diagnosis systems have been designed to aid radiologists detecting and classifying abnormalities. The first part of this thesi...
Conference Paper
PURPOSE To compare effectiveness of a novel interactive CAD system for detecting masses in screening mammograms to the current practice of using prompts. METHOD AND MATERIALS We investigated a novel method of presenting CAD results to radiologists. Instead of displaying prompts after unaided inspection, information is provided on request when a su...
Article
Full-text available
To improve cancer detection in mammography, breast examinations usually consist of two views per breast. In order to combine information from both views, corresponding regions in the views need to be matched. In 3D digital breast tomosynthesis (DBT), this may be a difficult and time-consuming task for radiologists, because many slices have to be in...
Article
Full-text available
When reading mammograms, radiologists combine information from multiple views to detect abnormalities. Most computer-aided detection (CAD) systems, however, use primitive methods for inclusion of multiview context or analyze each view independently. In previous research it was found that in mammography lesion-based detection performance of CAD syst...
Article
Full-text available
The reduction of false positive marks in breast mass CAD is an active area of research. Typically, the problem can be approached by either developing more discriminative features or by employing different classifier designs. Usually one intends to find an optimal combination of classifier configuration and small number of features to ensure high cl...
Article
Full-text available
Background. Contrary to what may be expected, finding abnormalities in complex images like pulmonary nodules in chest radiographs is not dominated by time-consuming search strategies but by an almost immediate global interpretation. This was already known in the nineteen-seventies from experiments with briefly flashed chest radiographs. Later on, e...
Chapter
Breast cancer is the most common form of cancer among women world-wide. One in nine women will be diagnosed with a form of breast cancer in her lifetime. In an effort to diagnose cancer at an early stage, screening programs have been introduced by using periodic mammographic examinations in asymptomatic women. In evaluating screening cases, radiolo...
Article
Full-text available
To evaluate an interactive computer-aided detection (CAD) system for reading mammograms to improve decision making. A dedicated mammographic workstation has been developed in which readers can probe image locations for the presence of CAD information. If present, CAD findings are displayed with the computed malignancy rating. A reader study was con...
Conference Paper
Full-text available
Medical image interpretation is a difficult problem for which human interpreters, radiologists in this case, are normally better equipped than computers. However, there are many clinical situations where radiologist’s performance is suboptimal, yielding a need for exploitation of computer-based interpretation for assistance. A typical example of su...
Conference Paper
In this paper, we study the use of Bayesian networks to interpret breast X-ray images in the context of breast-cancer screening. In particular, we investigate the performance of a manually developed Bayesian network under various discretisation schemes to check whether the probabilistic parameters in the initial manual network with continuous featu...
Conference Paper
Full-text available
Mammographic analysis is a difficult task due to the com- plexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by computer decision-making tools. Probabilistic modelling based on Bayesian networks is among the suitable tools, as it allows for the formalization of the uncertainty about param...
Article
Full-text available
Mammographic reading by radiologists requires the comparison of at least two breast projections (views) for the detection and the diagnosis of breast abnormalities. Despite their reported potential to support radiologists, most mammographic computer-aided detection (CAD) systems have a major limitation: as opposed to the radiologist's practice, com...
Article
Full-text available
Most computer aided detection (CAD) systems for mammographic mass detection display all suspicious regions identified by computer algorithms and are mainly intended to avoid missing cancers due to perceptual oversights. Considering that interpretation failure is recognized to be a more common cause of missing cancers in screening than perceptual ov...
Conference Paper
PURPOSE To study effectiveness of an interactive CAD system for reading mammograms, in which readers may probe regions for CAD information to improve decision making. METHOD AND MATERIALS Interactive use of CAD was studied using a dedicated mammographic workstation. Readers could probe image locations for presence of CAD information using a mouse....
Conference Paper
PURPOSE In an interactive CAD system for reading mammograms users may probe regions for CAD information to improve decision making. Probed locations reveal information about the detection process. The purpose of this study is to assess to what extent missed lesions in an observer study were due to perception rather than interpretation failure. ME...
Conference Paper
Full-text available
In reading mammograms, radiologists judge for the presence of a lesion by comparing at least two breast projections (views) as a lesion is to be observed in both of them. Most computer-aided detection (CAD) systems, on the other hand, treat single views independently and thus they fail to account for the interaction between the breast views. Follow...
Conference Paper
In many prediction problems it is known that the response variable depends monotonically on most of the explanatory variables but not on all. Often such partially monotone problems cannot be accurately solved by unconstrained methods such as standard neural networks. In this paper we propose so-called MIN-MAX networks that are partially monotone by...
Conference Paper
A mammographic screening workstation has been developed in which CAD results for mass detection are presented fundamentally different than in current practice. Instead of displaying all CAD findings as prompts the reader can probe image regions for the presence of CAD information. The aim of the system is to help radiologists with decision making r...
Article
Full-text available
Most of the current CAD systems detect suspicious mass regions independently in single views. In this paper we present a method to match corresponding regions in mediolateral oblique (MLO) and craniocaudal (CC) mammographic views of the breast. For every possible combination of mass regions in the MLO view and CC view, a number of features are comp...
Conference Paper
Full-text available
The goal of breast cancer screening programs is to detect cancers at an early (preclinical) stage, by using periodic mammographic examinations in asymptomatic women. In evaluating cases, mammographers insist on reading multiple images (at least two) of each breast as a cancerous lesion tends to be observed in different breast projections (views). M...
Conference Paper
Full-text available
In this paper, we compare two state-of-the-art classification techniques characterizing masses as either benign or malignant, using a dataset consisting of 271 cases (131 benign and 140 malignant), containing both a MLO and CC view. For suspect regions in a digitized mammogram, 12 out of 81 calculated image features have been selected for investiga...
Article
Full-text available
PURPOSE/AIM To experience the use of an interactive computer-aided decision support system for the detection of mammographic masses. To demonstrate the real-time classification of breast lesions. CONTENT ORGANIZATION The idea of using CAD in an interactive way will be explained. Then a case review will be offered, in which participants evaluate a...

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