The role of mammography in breast cancer radiomics

Mammography is still the only screening method for breast cancer. Although digital mammography is the most common and widely used method for detecting breast cancer, it is ineffective at detecting and assessing intratumoral heterogeneity. Due to the small size of the tissue sample or tumor, biopsies often fail to represent the entire tumor. For this reason, selecting a treatment and determining a patients prognosis becomes difficult. In this case, medical imaging is a noninvasive approach that can provide a more comprehensive view of the entire tumor, act as a virtual biopsy, and be useful for monitoring disease progression and response to therapy. Radiomics with texture analysis allows you to look at an image as a group of numerical data, moving beyond the usual visual perception and into a deeper analysis of digital, pixel data to improve the accuracy of differential diagnosis. Radiogenomics is a natural extension of radiomics that focuses on determining gene expression based on radiologic tumor phenotype. The purpose of this review is to evaluate the role of mammography in breast cancer radiomics and radiogenomics. The article presents a literature review of relevant Russian scientific articles found in databases such as PubMed, Medline, Springer, eLibrary, and Google Scholar. The information obtained was then pooled, structured, and analyzed to examine the role of mammography in breast cancer screening radiomics.

CMOS Digital Pixel Sensors With In-Pixel Analog-To-Digital Conversion

This thesis deals with the designing of CMOS image sensors with in-pixel analog-to-digital conversion. A 2-stage memory write scheme for Pulse-Width-Modulation digital pixel sensors is proposed. It utilizes the characteristics of Gray-code counters and partitions a single data write operation into two separated write operations such that the size of the in-pixel memory can be significantly reduced. A Pulse-Frequency-Modulation pixel significantly reduces the integration time without sacrificing the dynamic range. Finally, a Pulse-Frequency-Modulation Digital Pixel Sensor with an in-pixel variable reference voltage is proposed. As compared with conventional Pulse-Frequency-Modulation pixels, the proposed architecture improves the dynamic range by adaptively adjusting the reference voltage in the pixel. All proposed digital pixel sensors are designed in TSMC-0.18μm 6-Metal 1-Poly 1.8 V CMOS technology and analyzed using Spectre from Cadence Design Systems with BSIM3V3 device models. The effectiveness of the proposed digital pixel sensors is validated using simultation.

CMOS Digital Pixel Sensors With In-Pixel Analog-To-Digital Conversion

This thesis deals with the designing of CMOS image sensors with in-pixel analog-to-digital conversion. A 2-stage memory write scheme for Pulse-Width-Modulation digital pixel sensors is proposed. It utilizes the characteristics of Gray-code counters and partitions a single data write operation into two separated write operations such that the size of the in-pixel memory can be significantly reduced. A Pulse-Frequency-Modulation pixel significantly reduces the integration time without sacrificing the dynamic range. Finally, a Pulse-Frequency-Modulation Digital Pixel Sensor with an in-pixel variable reference voltage is proposed. As compared with conventional Pulse-Frequency-Modulation pixels, the proposed architecture improves the dynamic range by adaptively adjusting the reference voltage in the pixel. All proposed digital pixel sensors are designed in TSMC-0.18μm 6-Metal 1-Poly 1.8 V CMOS technology and analyzed using Spectre from Cadence Design Systems with BSIM3V3 device models. The effectiveness of the proposed digital pixel sensors is validated using simultation.

Measurement of Water Leaving Reflectance Using a Digital Camera Based on Multiple Reflectance Reference Cards

With the development of citizen science, digital cameras and smartphones are increasingly utilized in water quality monitoring. The smartphone application HydroColor quantitatively retrieves water quality parameters from digital images. HydroColor assumes a linear relationship between the digital pixel number (DN) and incident radiance and applies a grey reference card to derive water leaving reflectance. However, image DNs change with incident light brightness non-linearly, according to a power function. We developed an improved method for observing and calculating water leaving reflectance from digital images based on multiple reflectance reference cards. The method was applied to acquire water, sky, and reflectance reference card images using a Cannon 50D digital camera at 31 sampling stations; the results were validated using synchronously measured water leaving reflectance using a field spectrometer. The R2 for the red, green, and blue color bands were 0.94, 0.95, 0.94, and the mean relative errors were 27.6%, 29.8%, 31.8%, respectively. The validation results confirm that this method can derive accurate water leaving reflectance, especially when compared with the results derived by HydroColor, which systematically overestimates water leaving reflectance. Our results provide a more accurate theoretical foundation for quantitative water quality monitoring using digital and smartphone cameras.