Breast Cancer Research Topics

Breast Cancer Research Topics is one of the most significant researches to detect the breast cancer at the early stage. So we propose this to our research to enhance the identification of the disease. Here we provide some of the topics that are related to DBT and its significance:

Define Digital Breast Tomosynthesis (DBT)

Breast Cancer Research (DBT) picks multiple pictures of your breast on the basis of a more angles than a regular mammogram, making a most described image. DBT displays cancer when it possibly has or else “hidden” in thick breast cells.

What is Digital Breast Tomosynthesis (DBT)?

After the definition we see the in-depth description of Digital Breast Tomosynthesis, it is a method that permits healthcare specialists to observe multiple images of the breast instead of usual single image gained with the conventional mammogram. The Conventional mammograms offer doctors with a single 2D image to estimate the breast.

Where Digital Breast Tomosynthesis (DBT) used?

Next to the in-depth description of Digital Breast Tomosynthesis (DBT) we discuss where to incorporate it. It helps in the early identification and analysis of breast disease. The X-ray test assists doctors to analysis and handle medical situations. It reveals you to a minimum dose of ionizing radiation to generate pictures inward to the body.

Why Digital Breast Tomosynthesis (DBT) technology proposed? , previous technology issues

In this research we proposed the Breast Cancer Research (DBT) technology and is compared with several previous technology issues to tackle. This technology was proposed as an effective improvement in breast imaging to overcome some problems that is linked with the traditional 2D mammography. The previous technology problems are inaccurate identification, fails in image quality assessment, insufficient precautions and inadequate segmentation.

Algorithms / protocols

DBT is proposed in this research and it overcomes few of the previous technology issues, now we look through the algorithms/protocols to be utilized for this research. The methods to be utilized are Improved Canny Operator (ICO), Semi-Supervised CNN (SS CNN), Enhanced Contrast Limited Adaptive Histogram (ECLAH), Residual U Network (Res U-Net), Multistage Selective Convolution Filter (MSCF), SENSE Squeeze Excitation Network (DENSE SE-Net) and You Only Look Once (YOLO v7).

Comparative study / Analysis

The DBT is one of the advanced technologies to detect the breast cancer at early stage. Here we compared this with various methods like:

Enhanced Contrast Limited Adaptive Histogram is utilized for enhancing the visibility level of foggy image or video and it also employs a clip limit to avoid the image over-saturation.
YOLO-V7 is the new version of YOLO object detection method. It is a single-stage detection method and it has the capacity to identify multiple objects in a single image.
Res U-Net is a residual neural network structure and it is an creative method that made for classification of image and it has the capacity to generate exact segmentation maps and to manage high-resolution images.

Simulation results / Parameters

The proposed DBT technology is now compared with various metrics to estimate its performance. The metrics to be used are Recall, ROC curve, Accuracy, F1-Score and precision are to be used in this research.

Dataset LINKS / Important URL

The DBT technology is now widely used in many of the medical fields to identify the breast cancer. In this we offer some important links to be preferred for the understanding of DBT:

Digital Breast Tomosynthesis (DBT) Applications

The applications to be utilized for breast tomosynthesis are employed to achieve screening mammography, this screening mammography over breast tomosynthesis has been shown to enhance accuracy and to decrease false positive rates in women of all breast masses and it identifies the cancer at the early stage in women without any indications.

Topology for Digital Breast Tomosynthesis (DBT)

Now we see the topology to be utilized for the DBT, it is a 3D breast imaging method which is employed for the breast cancer screening and analysis; it is the more effective than the traditional 2D mammography. The topology for DBT contains the utilization of X-ray imaging and generalized apparatus to generate a sequence of lean images of the breast, permitting for enhanced identification of breast anomalies and best visualization.

Environment in Digital Breast Tomosynthesis (DBT)

The environment that we utilized for DBT is Qualified personnel, Room Design, Patient Comfort, Radiation Safety, Quality Control, Compression Device, Positioning and Alignment AIDS, Image Processing Software and Image Acquisition Protocols.

Simulation tools

Digital Breast Tomosynthesis is proposed in this research and we tackle many previous technology issues to overcome. The software requirement to be employed for this research is that we execute this by using the programming language like python 3.11.4 and then is operated by the OS Windows 10 [64bit].

Results

DBT is now widely utilized to identify the breast cancer at early stage. This proposed system tackles some existing technologies. DBT is an enhanced technology that tackles problems linked with the previous techniques and to overcome this. And then we compare this with various methods and metrics to obtain the correct findings.

Breast Cancer Research Research Ideas:

The following are the research topics that are related to the Digital Breast Tomosynthesis and we have to use these research topics to interpret and clarify the justifications about DBT:

A Convolutional Neural Network Model for Image Enhancement of Extremely Dense Breast Tissue in Digital Breast Tomosynthesis Images
An Image Denoising Model using Deep Learning for Digital Breast Tomosynthesis Images
Classification of benign and malignant tumors in Digital Breast Tomosynthesis images using Radiomic-based methods
A Comparative Study of Unsharp Masking Filters for Enhancement of Digital Breast Tomosynthesis Images
Truncated Projection Artifacts Removal in Digital Breast Tomosynthesis
Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels
SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis
Early screening outcomes before, during, and after a randomized controlled trial with digital breast tomosynthesis
Threshold in breast compression reduction for full-field digital mammography and digital breast tomosynthesis
Development of an Intratumoral and Peritumoral Radiomics Nomogram Using Digital Breast Tomosynthesis for Preoperative Assessment of Lymphovascular Invasion in Invasive Breast Cancer
Digital breast tomosynthesis versus X-ray of the breast specimen for intraoperative margin assessment: A randomized trial
Management of screening-detected lobular neoplasia in the era of digital breast tomosynthesis: A preliminary study
Imaging characteristics of interval cancers detected on Full Field Digital Mammography (FFDM) versus Digital Breast Tomosynthesis (DBT)
Feasibility of predicting a screening digital breast tomosynthesis recall using features extracted from the electronic medical record
Digital Breast Tomosynthesis: A Decade of Practice in Review
Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial
Eye radiation dose from breast cancer screening using full field digital mammography and digital breast tomosynthesis: A phantom study
Resolution aware nonconvex quasinorm iterative digital breast tomosynthesis imaging
Preoperative localization of breast lesions: Comparing digital breast tomosynthesis-guided radioactive seed localization versus standard 2D stereotactic radioactive seed localization
Artificial intelligence for digital breast tomosynthesis: Impact on diagnostic performance, reading times, and workload in the era of personalized screening
Lesion-specific exposure parameters for breast cancer diagnosis on digital breast tomosynthesis and full-field digital mammography
CAPNet: Context attention pyramid network for computer-aided detection of microcalcification clusters in digital breast tomosynthesis
Fabrication of 3D printed patient-derived anthropomorphic breast phantoms for mammography and digital breast tomosynthesis: Imaging assessment with clinical X-ray spectra
Evaluation of patient dose during a digital breast tomosynthesis
A comparative efficacy study of diagnostic digital breast tomosynthesis and digital mammography in BI-RADS 4 breast cancer diagnosis
Radiomics Analysis on Digital Breast Tomosynthesis: Preoperative Evaluation of Lymphovascular Invasion Status in Invasive Breast Cancer

27.Evaluation of average glandular dose and investigation of the relationship with compressed breast thickness for full-field digital mammography and digital breast tomosynthesis

Comparing the performance of full-field digital mammography and digital breast tomosynthesis in the post-treatment surveillance of patients with a history of breast cancer: A retrospective study
Mammography and Digital Breast Tomosynthesis in Granulomatous and Nongranulomatous Mastitis
An individual participant data meta-analysis of breast cancer detection and recall rates for digital breast tomosynthesis versus digital mammography population screening
Full-field digital mammography and digital breast tomosynthesis: The relationship between compression force, image quality and radiation dose
Impact of age and breast thickness on mean glandular dose of standard digital mammography and digital breast tomosynthesis
Comparison of Abbreviated Breast MRI vs Digital Breast Tomosynthesis for Breast Cancer Detection among Women with a History of Breast Cancer
Image quality for digital breast tomosynthesis (dbt): a statistical low contrast detail approach for synthesized and reconstructed planes
Typical values for different digital breast tomosynthesis systems evaluated in a multicenter study
Deeplook: a new artificial intelligence computer aided detection system for digital breast tomosynthesis
Typical values for z-resolution of different digital breast tomosynthesis systems evaluated in a multicenter study
Analysis, using a dose tracking system (dts), of digital tomosynthesis-guided breast biopsy procedures performed in 3 different centres
Digital breast tomosynthesis-guided vacuum-assisted biopsy of suspicious calcifications at different sites within one breast: Is biopsy of more than one location needed?
Clinical performance and patient outcomes in upright Digital Breast Tomosynthesis-guided Vacuum-Assisted Breast Biopsy and Prone stereotactic system: A review
HTA62 Efficacy and Safety of Digital Tomosynthesis As a Screening Test for Breast Cancer
Single Center Evaluation of Comparative Breast Radiation dose of Contrast Enhanced Digital Mammography (CEDM), Digital Mammography (DM) and Digital Breast Tomosynthesis (DBT)
P193 Intraoperative specimen digital breast tomosynthesis as predictor of resection margin status in breast conserving surgery for breast cancer – first year experience
EE112 Cost-Effectiveness of Digital Breast Tomosynthesis in Mammography Screening in Women With High Breast Density From a Czech Perspective

45.French national diagnostic reference levels in digital mammography and digital breast tomosynthesis

Diagnostic accuracy of radiography, digital breast tomosynthesis, micro-CT and ultrasound for margin assessment during breast surgery: A systematic review and meta-analysis
Local diagnostic reference levels (LDRLs) for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) procedures in Morocco
MT30 A Systematic Review of Clinical and Economic Literature of Breast Cancer Screening with Digital Breast Tomosynthesis (DBT) Combined With Synthesised Two-Dimensional Mammography (S2D) Versus Digital Mammography Alone (DM)
Letter response relatively to the paper entitled: Assessment of the uterine dose in digital mammography and digital breast tomosynthesis
Reply to “Critique of a Study on Breast Ultrasound as an Adjunct to Breast Tomosynthesis for Breast Cancer Screening and Diagnosis”