Embryo selection is a critical step in the process of in-vitro fertilisation in which embryologists choose the most viable embryos for transfer into the uterus. In recent years, numerous works have used computer vision to perform embryo selection. ...

The automatic registration of noninvasive second-harmonic generation microscopy to hematoxylin and eosin slides is a highly desired, yet still unsolved problem. The task is challenging because the second-harmonic images contain only partial ...

Achieving microscopy with large space-bandwidth products plays a key role in diagnostic imaging and is widely significant in the overall field of clinical practice. Among quantitative microscopy techniques, Fourier Ptychography (FP) provides a ...

• Generative Neural network to generate Fourier Ptychographic Microscopy phase maps.
• Low-resolution real and imaginary components of complex amplitude as GAN input.
• High-resolution, wide FoV phase-contrast reconstruction of ...

Ultra-fast optical pulses are the most ephemeral sensing paradigm ever devised, examining events over incredibly brief timescales with broadband illumination. A consequence of sensing at timescales lower than a picosecond is that pulse ...

• Ultrafast pulse characterization is built largely on auto-correlation datasets.
• Tensor iterative hard thresholding and gradient techniques demonstrate algorithmic superiority.
• These methods are applied to a condensed measurement ...

In the domain of medical image analysis, deep learning models are heralding a revolution, especially in detecting complex and nuanced features characteristic of diseases like tumors and cancers. However, the robustness and adaptability of these ...

• F2DA for stain normalization in histopathology and microscopic slides.
• Converting bounding box labels to precise segmentation for detailed analysis.
• Framework using Multi-Axis attention for robust, multi-faceted malaria detection.

Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fast bacilli by fluorescence microscopy of sputum smears is a common tool for both tasks. ...

• First automated detection of Mtb bacteria with a dual fluorescence staining.
• The proposed network achieves excellent performance at localising bacteria in a field of view.
• Detection of Mtb cells stained with two fluorescence dyes ...

Recent advances in deep learning have transformed data-driven geoscientific analysis. In particular, the adoption of attention mechanism in deep learning has received considerable interest and shown impressive results that can surpass traditional ...

• This study proposes a novel attention-based deep learning workflow to advance quantitative petrography.
• The Super Petrography model outperforms other conventional and deep learning methods for image super-resolution tasks.
• Multi-...

Inverse problems in image reconstruction are fundamentally complicated by unknown noise properties. Classical iterative deconvolution approaches amplify noise and require careful parameter selection for an optimal trade-off between sharpness and ...

Contrast-Enhanced Ultra-Sound (CEUS) has become a viable method for non-invasive, dynamic visualization in medical diagnostics, yet Ultrasound Localization Microscopy (ULM) has enabled a revolutionary breakthrough by offering ten times higher ...

The process of acquiring microscopic images in life sciences often results in image degradation and corruption, characterised by the presence of noise and blur, which poses significant challenges in accurately analysing and interpreting the ...

Overview of the proposed method for plant leaf epidermal imaging.

Here we propose and demonstrate the use of embedded speckle structured illumination microscopy for the non-destructive evaluation and 3D reconstruction of the plant ...

• An optodigital system for 3D visualization of plant leaf epidermis.
• Optically sectioned images of leaf epidermis with high axial resolution.
• An algorithm based on height segmentation for necrosis detection is presented.
• ...

Intricate characterisation of the leaf epidermal surface is of utmost importance in agricultural crop management. The epidermal surface serves as a plant's outermost interface with the environment and is responsible for several physiological ...

Breast cancer is one of the most prevalent cancers in women. Reliable pathology identification can help histopathologists make accurate diagnosis of breast cancer but require specialized histopathological knowledge and a significant ...

Stain color variation in histological images, caused by a variety of factors, is a challenge not only for the visual diagnosis of pathologists but also for cell segmentation algorithms. To eliminate the color variation, many stain normalization ...

Karyotyping is an important procedure to assess the possible existence of chromosomal abnormalities. However, because of the non-rigid nature, chromosomes are usually heavily curved in microscopic images and such deformed shapes hinder the ...

Diagnosing hematological malignancies requires identification and classification of white blood cells in peripheral blood smears. Domain shifts caused by different lab procedures, staining, illumination, and microscope settings hamper the re-...

In recent years, the field of embryo imaging has seen an influx of work using machine learning. These works take advantage of large microscopy datasets collected by fertility clinics as routine practice through relatively standardised imaging ...

Dealing with limited medical imagery data by deep neural networks is of a great concern. Obtaining large-scale labelled images requires expertise, is laborious and time consuming, and remains a challenge in medical applications. In this paper, we ...

We propose a method to nonrigidly align a three-dimensional (3D) volumetric image with a two-dimensional (2D) planar image representing a projection of the deformed volume. The application in mind comes from biological studies in which 2D ...

Biomedical images are noisy. The imaging equipment itself has physical limitations, and the consequent experimental trade-offs between signal-to-noise ratio, acquisition speed, and imaging depth exacerbate the problem. Denoising is, therefore, an ...

• Parameter sensitivity analysis (SA) and Uncertainty Quantification (UQ) was evaluated in Pathology image analysis workflows.

Background and Objective:Computerized pathology image analysis is an important tool in research and clinical settings, which enables quantitative tissue characterization and can assist a pathologist’s evaluation. The aim ...