Improving the Robustness of Diagnostic Accuracy Results By Asking Study Readers to Further Distinguish Subjects Who Appear to be Without the Condition Of Interest.

Rationale And Objectives: In diagnostic accuracy studies, cases in which a reader does not see the condition of interest are often given the same score for ROC analysis (e.g. confidence score of 0%).

Structure Correction for Robust Volume Segmentation in Presence of Tumors.

CNN based lung segmentation models in absence of diverse training dataset fail to segment lung volumes in presence of severe pathologies such as large masses, scars, and tumors. To rectify this problem, we propose a multi-stage algorithm for lung volume segmentation from CT scans. The algorithm uses a 3D CNN in the first stage to obtain a coarse segmentation of the left and right lungs.

Prospective Pilot Evaluation of Radiologists and Computer-aided Pulmonary Nodule Detection on Ultra-low-Dose CT With Tin Filtration.

Purpose: The aim of this study was to evaluate the ability of computer-aided detection (CAD) and human readers to detect pulmonary nodules ≥5 mm using 100 kV ultra-low-dose computed tomography (ULDCT) utilizing a tin filter.

Materials And Methods: After informed consent, 55 patients prospectively underwent standard-dose chest CT (SDCT) using 120 kV followed by ULDCT using 100 kV/tin. Reference nodules ≥5 mm were identified by a thoracic radiologist using SDCT.

CT colonography: effect of computer-aided detection of colonic polyps as a second and concurrent reader for general radiologists with moderate experience in CT colonography.

Objectives: To assess the effectiveness of computer-aided detection (CAD) as a second reader or concurrent reader in helping radiologists who are moderately experienced in computed tomographic colonography (CTC) to detect colorectal polyps.

Methods: Seventy CTC datasets (34 patients: 66 polyps ≥6 mm; 36 patients: no abnormalities) were retrospectively reviewed by seven radiologists with moderate CTC experience. After primary unassisted evaluation, a CAD second read and, after a time interval of ≥4 weeks, a CAD concurrent read were performed.

Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.

Objective: The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT.

Materials And Methods: For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)).

Time-efficient CT colonography interpretation using an advanced image-gallery-based, computer-aided "first-reader" workflow for the detection of colorectal adenomas.

Objectives: To assess the performance of an advanced "first-reader" workflow for computer-aided detection (CAD) of colorectal adenomas ≥ 6 mm at computed tomographic colonography (CTC) in a low-prevalence cohort.

Methods: A total of 616 colonoscopy-validated CTC patient-datasets were retrospectively reviewed by a radiologist using a "first-reader" CAD workflow. CAD detections were presented as galleries of six automatically generated two-dimensional (2D) and three-dimensional (3D) images together with interactive 3D target views and 2D multiplanar views of the complete dataset.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume.

Objective: To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume.

Methods: A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD.

Improved efficiency of CT interpretation using an automated lung nodule matching program.

Objective: The purpose of this study was to assess the impact of an automated program on improvement in lung nodule matching efficiency.

Materials And Methods: Four thoracic radiologists independently reviewed two serial chest CT examinations from each of 57 patients. Each radiologist performed timed manual lung nodule matching.

Impact of a computer-aided detection (CAD) system integrated into a picture archiving and communication system (PACS) on reader sensitivity and efficiency for the detection of lung nodules in thoracic CT exams.

The objective of this study is to assess the impact on nodule detection and efficiency using a computer-aided detection (CAD) device seamlessly integrated into a commercially available picture archiving and communication system (PACS). Forty-eight consecutive low-dose thoracic computed tomography studies were retrospectively included from an ongoing multi-institutional screening study. CAD results were sent to PACS as a separate image series for each study.

Computer-aided detection of colorectal polyps in CT colonography with and without fecal tagging: a stand-alone evaluation.

Purpose: To evaluate the stand-alone performance of a computer-aided detection (CAD) algorithm for colorectal polyps in a large heterogeneous CT colonography (CTC) database that included both tagged and untagged datasets.

Methods: Written, informed consent was waived for this institutional review board-approved, HIPAA-compliant retrospective study. CTC datasets from 2063 patients were assigned to training (n = 374) and testing (n = 1689).

Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

Purpose: To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA).

Materials And Methods: We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE.

Sensitivity of CT colonography for nonpolypoid colorectal lesions interpreted by human readers and with computer-aided detection.

Objective: The purpose of our study was to determine the sensitivity of CT colonography (CTC) interpreted by human readers and with computer-aided detection (CAD) for genuinely nonpolypoid colorectal lesions, defined as 2 mm or less in lesion height at colonoscopy.

Materials And Methods: A computerized database search for a 33-month period found 21 patients who had undergone both colonoscopy and CTC and who had a total of 23 genuinely nonpolypoid colorectal lesions: eight adenomas (9-30 mm in width), 10 stage Tis or T1 adenocarcinomas (10-25 mm), and five nonadenomatous lesions (8-20 mm). CTC was performed using a cathartic preparation and fecal tagging and was interpreted by experienced readers in a blinded manner using a primary 3D method and with CAD.

Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings.

Purpose: To determine whether computer-aided detection (CAD) applied to computed tomographic (CT) colonography can help improve sensitivity of polyp detection by less-experienced radiologist readers, with colonoscopy or consensus used as the reference standard.

Materials And Methods: The release of the CT colonographic studies was approved by the individual institutional review boards of each institution. Institutions from the United States were HIPAA compliant.

Hierarchical part-based detection of 3D flexible tubes: application to CT colonoscopy.

In this paper, we present a learning-based method for the detection and segmentation of 3D free-form tubular structures, such as the rectal tubes in CT colonoscopy. This method can be used to reduce the false alarms introduced by rectal tubes in current polyp detection algorithms. The method is hierarchical, detecting parts of the tube in increasing order of complexity, from tube cross sections and tube segments to the whole flexible tube.

Symmetric curvature patterns for colonic polyp detection.

A novel approach for generating a set of features derived from properties of patterns of curvature is introduced as a part of a computer aided colonic polyp detection system. The resulting sensitivity was 84% with 4.8 false positives per volume on an independent test set of 72 patients (56 polyps).

Effect of computer-aided detection as a second reader in multidetector-row CT colonography.

Our purpose was to assess the effect of computer-aided detection (CAD) on lesion detection as a second reader in computed tomographic colonography, and to compare the influence of CAD on the performance of readers with different levels of expertise. Fifty-two CT colonography patient data-sets (37 patients: 55 endoscopically confirmed polyps > or =0.5 cm, seven cancers; 15 patients: no abnormalities) were retrospectively reviewed by four radiologists (two expert, two nonexpert).