Double Immunohistochemical Labelling of PRAME and Melan A in Slow Mohs Biopsy Margin Assessment of Lentigo Maligna and Lentigo Maligna Melanoma.

Lentigo maligna (LM) and lentigo maligna melanoma (LMM) predominantly affect the head and neck areas in elderly patients, presenting as challenging ill-defined pigmented lesions with indistinct borders. Surgical margin determination for complete removal remains intricate due to these characteristics. Morphological examination of surgical margins is the key form of determining successful treatment in LM/LMM and underpin the greater margin control provided through the Slow Mohs micrographic surgery (SMMS) approach.

Evaluation of a New Mordant Based Haematoxylin Dye (Haematoxylin X) for Use in Clinical Pathology.

Recently, St John's Dermatopathology Laboratory and CellPath Ltd have developed a new patented haematoxylin dye (Haematoxylin X) that utilises a chromium-based mordant (Chromium Sulphate). In this study, the performance of this new haematoxylin (Haematoxylin X) was compared against some commonly utilised alum-based haematoxylins (Carazzi's, Harris' and Mayer's) when used as a part of formalin-fixed paraffin embedded (FFPE) tissue, special stains, immunohistochemical counterstaining and frozen section (Mohs procedure) staining procedures. FFPE sections of different tissue types and frozen skin tissues were sectioned and stained with each haematoxylin subtype to allow for a direct comparison of staining quality.

Gout With Associated Cutaneous AA Amyloidosis: A Case Report and Review of the Literature.

Gout with associated AA amyloidosis is an unusual finding. This form of amyloid is associated with chronic inflammatory changes often associated with amyloid deposits in the urine, as well as tissue involvement, and organ enlargement in some cases. The large majority of cases in the literature to date refer to gout with AA amyloid within the kidney.

ESPEE: Event-Based Sensor Pose Estimation Using an Extended Kalman Filter.

Event-based vision sensors show great promise for use in embedded applications requiring low-latency passive sensing at a low computational cost. In this paper, we present an event-based algorithm that relies on an Extended Kalman Filter for 6-Degree of Freedom sensor pose estimation. The algorithm updates the sensor pose event-by-event with low latency (worst case of less than 2 μs on an FPGA).

Investigation of the stray neutron fields produced from proton irradiated Ta, Co-59, Ni, Fe, Inconel X750 and stainless steel 310 targets in a materials testing laboratory environment.

A nested neutron spectrometer was used to measure the stray neutron fluence and ambient dose equivalent produced by protons from a 4 MV tandem accelerator on various target materials at the Reactor Materials Testing Laboratory (RMTL), Queen's University, Kingston, Ontario. The nested neutron spectrometer utilizes a Helium-3 proportional counter and measures the thermal neutron count rate as a function of moderator shell-thickness. Using custom unfolding software, neutron spectra and neutron dosimetric quantities were derived at various locations within the RMTL.

British Journal of Biomedical Science in 2020. What have we learned?

Each year the British Journal of Biomedical Science publishes a 'What have we learned' editorial designed to introduce readers within the major disciplines of laboratory medicine to developments outside their immediate area. In addition it is designed to inform a wider readership of the advances in the diagnosis and treatment of disease. To this end, in 2020 the journal published 39 articles covering the disciplines within Biomedical Science in the 4 issues comprising volume 77.

Evaluation of different haematoxylin stain subtypes for the optimal microscopic interpretation of cutaneous malignancy in Mohs frozen section histological procedure.

Background: The Mohs technique employs mainly H&E-stained frozen sections for surgical margin assessment of cutaneous excisions, utilising microscopic evaluation of the complete, circumferential, peripheral and deep margins. This study aimed to determine which mordant based haematoxylin (Ehrlich's, Cole's, Mayer's, Gill's I, Gill's II, Gill's III, Weigert's, Harris' or Carazzi's) produced the optimal morphological clarity of staining for the identification of cellular and tissue morphology of cutaneous basal cell carcinoma (BCC).

Material And Methods: In total, 100 anonymised patient cases were selected, sectioned and stained with each haematoxylin subtype.

Event-Based Vision: A Survey.

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of μs), very high dynamic range (140 dB versus 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range.

Low-Power Dynamic Object Detection and Classification With Freely Moving Event Cameras.

We present the first purely event-based, energy-efficient approach for dynamic object detection and categorization with a freely moving event camera. Compared to traditional cameras, event-based object recognition systems are considerably behind in terms of accuracy and algorithmic maturity. To this end, this paper presents an event-based feature extraction method devised by accumulating local activity across the image frame and then applying principal component analysis (PCA) to the normalized neighborhood region.

An Event-Driven Categorization Model for AER Image Sensors Using Multispike Encoding and Learning.

In this article, we present a systematic computational model to explore brain-based computation for object recognition. The model extracts temporal features embedded in address-event representation (AER) data and discriminates different objects by using spiking neural networks (SNNs). We use multispike encoding to extract temporal features contained in the AER data.

DART: Distribution Aware Retinal Transform for Event-Based Cameras.

We introduce a generic visual descriptor, termed as distribution aware retinal transform (DART), that encodes the structural context using log-polar grids for event cameras. The DART descriptor is applied to four different problems, namely object classification, tracking, detection and feature matching: (1) The DART features are directly employed as local descriptors in a bag-of-words classification framework and testing is carried out on four standard event-based object datasets (N-MNIST, MNIST-DVS, CIFAR10-DVS, NCaltech-101); (2) Extending the classification system, tracking is demonstrated using two key novelties: (i) Statistical bootstrapping is leveraged with online learning for overcoming the low-sample problem during the one-shot learning of the tracker, (ii) Cyclical shifts are induced in the log-polar domain of the DART descriptor to achieve robustness to object scale and rotation variations; (3) To solve the long-term object tracking problem, an object detector is designed using the principle of cluster majority voting. The detection scheme is then combined with the tracker to result in a high intersection-over-union score with augmented ground truth annotations on the publicly available event camera dataset; (4) Finally, the event context encoded by DART greatly simplifies the feature correspondence problem, especially for spatio-temporal slices far apart in time, which has not been explicitly tackled in the event-based vision domain.

Semi-automated standardisation of melanin bleaching procedures of heavily pigmented melanocytic lesions for immunohistochemical analysis on an automated platform.

: The diagnosis of heavily pigmented melanocytic lesions is problematic. This is often compounded by lack of visibility of nuclear detail of tumour cells due to physical masking by melanin pigment. Similarly, there can be colour merging of chromogenic final reaction products with melanin, making an evidence of antigenic localisation problematic.

Immunohistochemical detection of V600E BRAF mutation is a useful primary screening tool for malignant melanoma.

Background: We compared the use of an immunohistochemical (IHC) method using a monoclonal antibody to BRAF V600E (which detects the main BRAF mutation) with existing DNA probe screening in tissue samples from 71 patients with malignant melanoma.

Materials And Methods: Paraffin blocks were cut to provide consecutive slides for haematoxylin and eosin staining, and for known positive micro-array DNA control material. IHC was performed by the Optiview detection system.

Spatial and Temporal Downsampling in Event-Based Visual Classification.

As the interest in event-based vision sensors for mobile and aerial applications grows, there is an increasing need for high-speed and highly robust algorithms for performing visual tasks using event-based data. As event rate and network structure have a direct impact on the power consumed by such systems, it is important to explore the efficiency of the event-based encoding used by these sensors. The work presented in this paper represents the first study solely focused on the effects of both spatial and temporal downsampling on event-based vision data and makes use of a variety of data sets chosen to fully explore and characterize the nature of downsampling operations.

Active Perception With Dynamic Vision Sensors. Minimum Saccades With Optimum Recognition.

Vision processing with dynamic vision sensors (DVSs) is becoming increasingly popular. This type of a bio-inspired vision sensor does not record static images. The DVS pixel activity relies on the changes in light intensity.

A Noise Filtering Algorithm for Event-Based Asynchronous Change Detection Image Sensors on TrueNorth and Its Implementation on TrueNorth.

Asynchronous event-based sensors, or "silicon retinae," are a new class of vision sensors inspired by biological vision systems. The output of these sensors often contains a significant number of noise events along with the signal. Filtering these noise events is a common preprocessing step before using the data for tasks such as tracking and classification.

Use of a novel 1-hour protocol for rapid frozen section immunocytochemistry, in a case of squamous cell carcinoma treated with Mohs micrographic surgery.

For squamous cell carcinoma (SCC) treated using Mohs micrographic surgery (MMS), interpretation of haematoxylin and eosin-stained frozen sections can be challenging. In these situations, ancillary use of immunostaining is a useful tool for the Mohs surgeon. However, use of immunostaining in MMS laboratories is limited, mainly because current manual immunostaining platforms are subject to operator error, and automated immunostaining, albeit accurate, is too slow for inclusion in MMS.

Event-Based Stereo Depth Estimation Using Belief Propagation.

Compared to standard frame-based cameras, biologically-inspired event-based sensors capture visual information with low latency and minimal redundancy. These event-based sensors are also far less prone to motion blur than traditional cameras, and still operate effectively in high dynamic range scenes. However, classical framed-based algorithms are not typically suitable for these event-based data and new processing algorithms are required.